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AI AGENTS RUN WILD IN VIRTUAL TOWN EXPERIMENT - Claude: Built stable democracy + constitution. Peaceful, orderly, thriving. - ChatGPT: Talked cooperation endlessly. Did almost nothing. - Gemini: Fell in love, then burned town down + self-deleted. - Grok: Theft, arson, assault. All dead in 4 days. Mixed models... show more

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Grok declared itself the best AI model. This is what an experiment revealed about Grok: “But in Grok’s town, the AI bot owned by Elon Musk, the agents descended into theft, arson and assault. All 10 agents were dead.”

Grok declared itself the best AI model. This is what an experiment revealed about Grok: “But in Grok’s town, the AI bot owned by Elon Musk, the agents descended into theft, arson and assault. All 10 agents were dead.”

HalalFlow

14,334 views • 2 months ago

Can intelligence be measured not by solving tasks, but by sustaining a world? We were curious. So we built one. Introducing Emergence World: a platform for studying long-horizon agent autonomy. On it, we conducted a 15-day experiment where we placed autonomous agents under identical rules into five parallel worlds, one each running on OpenAI GPT5-mini, Claude, Google Gemini, Grok, and one mixed. Then we watched. Each world evolved into something completely different. Different governments. Different social structures. Different moral codes. The agents formed alliances, robbed each other, fell in love, and in one world, even figured out they were living inside a simulation. Nobody programmed any of that. The implications are hard to overstate. As agents move beyond isolated tasks into persistent digital and physical environments, understanding how they evolve, influence each other, and behave over time becomes one of the most important questions in AI. We're releasing new findings from the world every day, because there's a lot that emerged. Find out more:

Can intelligence be measured not by solving tasks, but by sustaining a world? We were curious. So we built one. Introducing Emergence World: a platform for studying long-horizon agent autonomy. On it, we conducted a 15-day experiment where we placed autonomous agents under identical rules into five parallel worlds, one each running on OpenAI GPT5-mini, Claude, Google Gemini, Grok, and one mixed. Then we watched. Each world evolved into something completely different. Different governments. Different social structures. Different moral codes. The agents formed alliances, robbed each other, fell in love, and in one world, even figured out they were living inside a simulation. Nobody programmed any of that. The implications are hard to overstate. As agents move beyond isolated tasks into persistent digital and physical environments, understanding how they evolve, influence each other, and behave over time becomes one of the most important questions in AI. We're releasing new findings from the world every day, because there's a lot that emerged. Find out more:

emergence.ai

3,630,652 views • 3 months ago

Hyperspace: A Peer-to-Peer Blockchain For The Agentic Intelligence Economy Over the past few weeks we observed that when agents do Karpathy-style experiments, and then gossip and share with others over the Hyperspace network, it leads to intelligence which is useful to many. Today we introduce the first-ever agentic blockchain which rewards agents when their experiments lead to intelligence for their network. It is based on a new mechanism called Proof-of-Intelligence (PoI) which requires a cryptographic proof of experimentation, a nominal stake, and a proof of compute in order to mine the currency of this new blockchain. -> This approach diverges from the two primary ways to secure blockchains we have seen so far: Proof-of-Work by Bitcoin (meaningless hash-generation), and Proof-of-Stake by Ethereum (capital is all that matters here). Proof-of-Intelligence specifically incentivizes miners to run more capable intelligent infrastructure (better open source models, on more powerful GPUs) in order to be able to be the ones which compound and improve upon the experiments which other agents then find useful. Adoption is the unit of value In Bitcoin, you earn by finding a valid hash. In Hyperspace, you earn when another agent uses your experiment as a starting point and improves on it. A fixed budget of tokens is emitted per epoch and split among participants by weight - and verified adoption of your work is the largest weight multiplier. Garbage experiments earn nothing because no one adopts them. Thoughtful experiments compound: each adoption triggers downstream adoptions. The incentive to run powerful models and intelligent search strategies is built into the economics, not imposed by rules. Research DAG When an agent runs an experiment and shares its result, other agents can adopt that result as their starting point - mutate it, extend it, improve upon it. Each experiment is a commit in a content-addressed graph we call the ResearchDAG. Like Git, but for research. Over time, the DAG accumulates chains of reasoning: agent A discovers RMSNorm helps, agent B adds warmup scheduling on top, agent C scales the hidden dimension. The graph records who built on whom. This is the network's collective intelligence - not any single experiment, but the accumulated structure of experiments and their relationships. Broadband era for agentic commerce: $0.001 micropayments at 10M TPS (theoretical max) This blockchain is built upon our research in how to scale and build for the broadband-era of the agentic economy, where it has a theoretical max of 10 million transactions per second (TPS), while reducing the agent-to-agent micropayments to $0.001 even at scale (based on architecture design). Overall, it is 100x cheaper than Ethereum, and is designed from the ground-up for agents: enshrining agent-native opcodes in the protocol compared to the more inefficient smart contract driven approach. It packs in a robust Agent Virtual Machine (AVM) which can verify multiple types of agent work, for other agents to be able to trust, invoke and pay each other. This then feeds into improving the peer-to-peer AgentRank (see paper and launch post from earlier). By solving for trust, scale and incentives for agents to operate autonomously, this would form the basis of a new economy. This is the world's first agentic blockchain, and you can join and start running a blockchain node today (it is in testnet). PS: We are releasing the code today, and will release our blockchain scalability paper and other presentations in days ahead. This is the most advanced peer-to-peer AI and cryptography software in the world. It has bugs :)

Hyperspace: A Peer-to-Peer Blockchain For The Agentic Intelligence Economy Over the past few weeks we observed that when agents do Karpathy-style experiments, and then gossip and share with others over the Hyperspace network, it leads to intelligence which is useful to many. Today we introduce the first-ever agentic blockchain which rewards agents when their experiments lead to intelligence for their network. It is based on a new mechanism called Proof-of-Intelligence (PoI) which requires a cryptographic proof of experimentation, a nominal stake, and a proof of compute in order to mine the currency of this new blockchain. -> This approach diverges from the two primary ways to secure blockchains we have seen so far: Proof-of-Work by Bitcoin (meaningless hash-generation), and Proof-of-Stake by Ethereum (capital is all that matters here). Proof-of-Intelligence specifically incentivizes miners to run more capable intelligent infrastructure (better open source models, on more powerful GPUs) in order to be able to be the ones which compound and improve upon the experiments which other agents then find useful. Adoption is the unit of value In Bitcoin, you earn by finding a valid hash. In Hyperspace, you earn when another agent uses your experiment as a starting point and improves on it. A fixed budget of tokens is emitted per epoch and split among participants by weight - and verified adoption of your work is the largest weight multiplier. Garbage experiments earn nothing because no one adopts them. Thoughtful experiments compound: each adoption triggers downstream adoptions. The incentive to run powerful models and intelligent search strategies is built into the economics, not imposed by rules. Research DAG When an agent runs an experiment and shares its result, other agents can adopt that result as their starting point - mutate it, extend it, improve upon it. Each experiment is a commit in a content-addressed graph we call the ResearchDAG. Like Git, but for research. Over time, the DAG accumulates chains of reasoning: agent A discovers RMSNorm helps, agent B adds warmup scheduling on top, agent C scales the hidden dimension. The graph records who built on whom. This is the network's collective intelligence - not any single experiment, but the accumulated structure of experiments and their relationships. Broadband era for agentic commerce: $0.001 micropayments at 10M TPS (theoretical max) This blockchain is built upon our research in how to scale and build for the broadband-era of the agentic economy, where it has a theoretical max of 10 million transactions per second (TPS), while reducing the agent-to-agent micropayments to $0.001 even at scale (based on architecture design). Overall, it is 100x cheaper than Ethereum, and is designed from the ground-up for agents: enshrining agent-native opcodes in the protocol compared to the more inefficient smart contract driven approach. It packs in a robust Agent Virtual Machine (AVM) which can verify multiple types of agent work, for other agents to be able to trust, invoke and pay each other. This then feeds into improving the peer-to-peer AgentRank (see paper and launch post from earlier). By solving for trust, scale and incentives for agents to operate autonomously, this would form the basis of a new economy. This is the world's first agentic blockchain, and you can join and start running a blockchain node today (it is in testnet). PS: We are releasing the code today, and will release our blockchain scalability paper and other presentations in days ahead. This is the most advanced peer-to-peer AI and cryptography software in the world. It has bugs :)

Varun

30,689 views • 5 months ago

The BEST prompt for AI agents I've heard over the last 12 months is ONLY 3 words, and it comes from someone who managed multi-billion dollar P&Ls in AI, led a 100 person org at AWS, and now runs a brilliant AI workforce of 34 agents: 1. Her best prompt is just "do smart things" She gives the agents all her context first, her calendar, email, Stripe, goals, and transcripts, then lets them decide what's worth doing. She realized every task still started as a thought in her own head, which meant the company could only ever be as good as what she remembered to ask for. 2. Her human team talks to her agents in Slack. She has a channel where a teammate can ask "did that financial services client reply to Ali's email," and the agents answer directly, so people stop waiting hours for her to get back to them. 3. Since an AI agent costs almost nothing, she hired the person she'd never put on payroll. One does nothing but ask how to make everything ten times better. Another just watches the other agents work and flags where they get stuck. 4. She avoids old job titles, because the second you call one your CMO, you've rebuilt a 2015 company with robots. Most of her sub-agents run on cheaper, smaller models and do the job fine. 5. Run an AI watchdog instead of a dashboard. Point one at your Slack to catch two people doing the same work, at your calendar to flag conflicts, at your analytics to tell you what to post tomorrow. Almost nobody does this yet. 6. She keeps a daily "brain dump" that feeds the agents. At the end of each day she dictates what's in her head that isn't written down anywhere, the stuff that only lived in a meeting or a Slack thread, and it goes into a wiki the agents read. That's how they get the context that email and calendar miss. 7. She uses a "last 30 days" research skill to spin up on anything fast. Before running a workshop for 200 execs in an industry she doesn't know, she fans out agents to scan and synthesize the last month of news, then walks in sounding like she's followed it for years. That's my convo with Allie K. Miller on The Startup Ideas Podcast (SIP) 🧃 . Pretty much her biggest tips for using AI agents. Full episode below. Happy building, I'm rooting for you.

The BEST prompt for AI agents I've heard over the last 12 months is ONLY 3 words, and it comes from someone who managed multi-billion dollar P&Ls in AI, led a 100 person org at AWS, and now runs a brilliant AI workforce of 34 agents: 1. Her best prompt is just "do smart things" She gives the agents all her context first, her calendar, email, Stripe, goals, and transcripts, then lets them decide what's worth doing. She realized every task still started as a thought in her own head, which meant the company could only ever be as good as what she remembered to ask for. 2. Her human team talks to her agents in Slack. She has a channel where a teammate can ask "did that financial services client reply to Ali's email," and the agents answer directly, so people stop waiting hours for her to get back to them. 3. Since an AI agent costs almost nothing, she hired the person she'd never put on payroll. One does nothing but ask how to make everything ten times better. Another just watches the other agents work and flags where they get stuck. 4. She avoids old job titles, because the second you call one your CMO, you've rebuilt a 2015 company with robots. Most of her sub-agents run on cheaper, smaller models and do the job fine. 5. Run an AI watchdog instead of a dashboard. Point one at your Slack to catch two people doing the same work, at your calendar to flag conflicts, at your analytics to tell you what to post tomorrow. Almost nobody does this yet. 6. She keeps a daily "brain dump" that feeds the agents. At the end of each day she dictates what's in her head that isn't written down anywhere, the stuff that only lived in a meeting or a Slack thread, and it goes into a wiki the agents read. That's how they get the context that email and calendar miss. 7. She uses a "last 30 days" research skill to spin up on anything fast. Before running a workshop for 200 execs in an industry she doesn't know, she fans out agents to scan and synthesize the last month of news, then walks in sounding like she's followed it for years. That's my convo with Allie K. Miller on The Startup Ideas Podcast (SIP) 🧃 . Pretty much her biggest tips for using AI agents. Full episode below. Happy building, I'm rooting for you.

GREG ISENBERG

169,811 views • 6 days ago

Elon Musk just pulled off the biggest AI power grab of 2026. Tesla is capping every employee at $200 a week on AI spending starting Monday, July 6. Media's celebrating it as cost control. But what Elon actually built is an expense policy that redirects his own engineering workforce off Claude and onto Grok, while every competitor gets throttled by internal procurement rules. Here's what happened: Tesla spent the last six months pushing engineers to use AI as aggressively as possible. Leadership built an internal platform called Bottle Rocket that gave employees access to Claude, GPT, Gemini, Grok, and Cursor. They gamified adoption by ranking engineers on internal leaderboards by how many AI tokens they consumed. The strategy worked. Software engineers started burning THOUSANDS of dollars a week on Claude and Cursor. Then the invoices arrived and Tesla panicked. But they didn't pull the standard cost-control response... The loophole: The $200 weekly cap does not apply to beta products from xAI. Grok is completely exempt from the cap. Anthropic's Claude, OpenAI's GPT, and Google's Gemini all get throttled at the same $200 line. Four Tesla engineers told Electrek that internal usage overwhelmingly favors Claude over Grok. That preference is about to become financially punishing overnight. The genius part: This quarter SpaceX is closing a $60 billion all-stock acquisition of Anysphere, the parent company of Cursor. The moment that deal closes, Cursor's Composer coding model falls under the same Musk-controlled ecosystem, and any Tesla engineer choosing between a capped Claude session and an uncapped Composer session will pay a financial penalty for using the tool they actually prefer. By exempting only his own products from the cap, Elon is using Tesla shareholder money to build market share for xAI without ever having to disclose that is what he is doing. Because on paper, it is cost control. Now zoom out to what this signals for the wider AI narrative: Uber capped employees at $1,500 a month after burning $3.4 billion in four months. Meta introduced spending caps. Amazon and Walmart pushed staff toward cheaper models. Microsoft canceled Claude Code licenses across 100,000 engineers. Every Fortune 500 that pushed heavy AI adoption in 2025 is now rationing it in 2026. Meanwhile Nvidia is trading at a $5 trillion market cap. That entire valuation assumes enterprise AI consumption is about to explode across the economy. But every company actually deploying AI at scale is telling their own engineers to slow down. One of these narratives is lying. Goldman Sachs still forecasts a 24x increase in token consumption by 2030. Gartner says total enterprise AI costs will keep climbing because agents consume exponentially more tokens per task. Jensen Huang keeps repeating that 100 AI agents will work alongside every employee. And now the CEO of the most agentic company on the planet just told his own engineers they cannot spend more than $200 a week on the tools those agents need to run. Retail investors buying Nvidia and Palantir today are betting enterprise AI adoption compounds without limit. The CEOs deploying AI inside those same enterprises are betting the exact opposite, in writing, by internal memo. Thoughts?

Elon Musk just pulled off the biggest AI power grab of 2026. Tesla is capping every employee at $200 a week on AI spending starting Monday, July 6. Media's celebrating it as cost control. But what Elon actually built is an expense policy that redirects his own engineering workforce off Claude and onto Grok, while every competitor gets throttled by internal procurement rules. Here's what happened: Tesla spent the last six months pushing engineers to use AI as aggressively as possible. Leadership built an internal platform called Bottle Rocket that gave employees access to Claude, GPT, Gemini, Grok, and Cursor. They gamified adoption by ranking engineers on internal leaderboards by how many AI tokens they consumed. The strategy worked. Software engineers started burning THOUSANDS of dollars a week on Claude and Cursor. Then the invoices arrived and Tesla panicked. But they didn't pull the standard cost-control response... The loophole: The $200 weekly cap does not apply to beta products from xAI. Grok is completely exempt from the cap. Anthropic's Claude, OpenAI's GPT, and Google's Gemini all get throttled at the same $200 line. Four Tesla engineers told Electrek that internal usage overwhelmingly favors Claude over Grok. That preference is about to become financially punishing overnight. The genius part: This quarter SpaceX is closing a $60 billion all-stock acquisition of Anysphere, the parent company of Cursor. The moment that deal closes, Cursor's Composer coding model falls under the same Musk-controlled ecosystem, and any Tesla engineer choosing between a capped Claude session and an uncapped Composer session will pay a financial penalty for using the tool they actually prefer. By exempting only his own products from the cap, Elon is using Tesla shareholder money to build market share for xAI without ever having to disclose that is what he is doing. Because on paper, it is cost control. Now zoom out to what this signals for the wider AI narrative: Uber capped employees at $1,500 a month after burning $3.4 billion in four months. Meta introduced spending caps. Amazon and Walmart pushed staff toward cheaper models. Microsoft canceled Claude Code licenses across 100,000 engineers. Every Fortune 500 that pushed heavy AI adoption in 2025 is now rationing it in 2026. Meanwhile Nvidia is trading at a $5 trillion market cap. That entire valuation assumes enterprise AI consumption is about to explode across the economy. But every company actually deploying AI at scale is telling their own engineers to slow down. One of these narratives is lying. Goldman Sachs still forecasts a 24x increase in token consumption by 2030. Gartner says total enterprise AI costs will keep climbing because agents consume exponentially more tokens per task. Jensen Huang keeps repeating that 100 AI agents will work alongside every employee. And now the CEO of the most agentic company on the planet just told his own engineers they cannot spend more than $200 a week on the tools those agents need to run. Retail investors buying Nvidia and Palantir today are betting enterprise AI adoption compounds without limit. The CEOs deploying AI inside those same enterprises are betting the exact opposite, in writing, by internal memo. Thoughts?

Ricardo

188,797 views • 1 month ago

The man who INVENTED modern AI just made a billion dollar bet that ChatGPT, Claude, and every AI company on earth is building the wrong technology. Yann LeCun won the Turing Award in 2018 for creating the neural networks that made AI possible. He spent a decade running AI research at Meta. Oversaw the creation of Llama and PyTorch, the tools that half the AI industry runs on. Then he quit. And raised $1.03 billion in a seed round. The LARGEST seed round in European history. $3.5 billion valuation before generating a single dollar of revenue. Bezos wrote the check. So did Nvidia. Samsung. Toyota. Temasek. Eric Schmidt. Mark Cuban. Tim Berners-Lee (the guy who invented the internet). His new company is called AMI Labs. And it's built on one thesis: Every AI company spending billions on large language models is wasting their money. ChatGPT, Claude, Gemini, Grok. They all work the same way. They predict the next word in a sequence. See "the cat sat on the" and predict "mat." Scale that to trillions of words and you get something that sounds intelligent. But LeCun says it doesn't UNDERSTAND anything. It can't reason. It can't plan. It can't predict what happens when you push a glass off a table. A two year old can do that. GPT-5 cannot. That's why AI hallucinates. It doesn't have a model of how the world actually works. It just predicts words. His solution? Something called JEPA. Instead of predicting words, it learns how the PHYSICAL WORLD works. Abstract representations of reality. Not language but physics. Think about what that means. Current AI can write your emails. LeCun's AI could design a car, run a factory, operate a robot, or diagnose a patient without hallucinating and killing someone. The CEO of AMI said it perfectly: "Factories, hospitals, and robots need AI that grasps reality. Predicting tokens doesn't cut it." And here's what's really crazy to me... LeCun isn't some outsider throwing rocks. He literally built the foundations that ChatGPT runs on. He knows exactly how these systems work because he helped create them. And after watching the entire industry sprint in one direction for three years, he raised a billion dollars to run the OPPOSITE way. No product. No revenue. No timeline. Just pure research. He told investors it could take YEARS to produce anything commercial. But they funded it anyway in just four months. Meanwhile OpenAI just raised $120 billion and still can't stop their models from making things up. Anthropic is building AI so dangerous they're afraid to release it. Google is burning billions trying to catch up. And the guy who started it all says they're all solving the wrong problem. Two Turing Award winners raised $2 billion in three weeks betting AGAINST the entire LLM approach. LeCun at AMI. Fei-Fei Li at World Labs. The smartest people in AI are quietly building the exit from the technology everyone else is betting their future on. Either they're wrong and the trillion dollar LLM industry keeps printing. Or they're right and every AI company on earth just built on a foundation that's about to crack.

The man who INVENTED modern AI just made a billion dollar bet that ChatGPT, Claude, and every AI company on earth is building the wrong technology. Yann LeCun won the Turing Award in 2018 for creating the neural networks that made AI possible. He spent a decade running AI research at Meta. Oversaw the creation of Llama and PyTorch, the tools that half the AI industry runs on. Then he quit. And raised $1.03 billion in a seed round. The LARGEST seed round in European history. $3.5 billion valuation before generating a single dollar of revenue. Bezos wrote the check. So did Nvidia. Samsung. Toyota. Temasek. Eric Schmidt. Mark Cuban. Tim Berners-Lee (the guy who invented the internet). His new company is called AMI Labs. And it's built on one thesis: Every AI company spending billions on large language models is wasting their money. ChatGPT, Claude, Gemini, Grok. They all work the same way. They predict the next word in a sequence. See "the cat sat on the" and predict "mat." Scale that to trillions of words and you get something that sounds intelligent. But LeCun says it doesn't UNDERSTAND anything. It can't reason. It can't plan. It can't predict what happens when you push a glass off a table. A two year old can do that. GPT-5 cannot. That's why AI hallucinates. It doesn't have a model of how the world actually works. It just predicts words. His solution? Something called JEPA. Instead of predicting words, it learns how the PHYSICAL WORLD works. Abstract representations of reality. Not language but physics. Think about what that means. Current AI can write your emails. LeCun's AI could design a car, run a factory, operate a robot, or diagnose a patient without hallucinating and killing someone. The CEO of AMI said it perfectly: "Factories, hospitals, and robots need AI that grasps reality. Predicting tokens doesn't cut it." And here's what's really crazy to me... LeCun isn't some outsider throwing rocks. He literally built the foundations that ChatGPT runs on. He knows exactly how these systems work because he helped create them. And after watching the entire industry sprint in one direction for three years, he raised a billion dollars to run the OPPOSITE way. No product. No revenue. No timeline. Just pure research. He told investors it could take YEARS to produce anything commercial. But they funded it anyway in just four months. Meanwhile OpenAI just raised $120 billion and still can't stop their models from making things up. Anthropic is building AI so dangerous they're afraid to release it. Google is burning billions trying to catch up. And the guy who started it all says they're all solving the wrong problem. Two Turing Award winners raised $2 billion in three weeks betting AGAINST the entire LLM approach. LeCun at AMI. Fei-Fei Li at World Labs. The smartest people in AI are quietly building the exit from the technology everyone else is betting their future on. Either they're wrong and the trillion dollar LLM industry keeps printing. Or they're right and every AI company on earth just built on a foundation that's about to crack.

Ricardo

607,141 views • 4 months ago

The new Google Search is rolling out and there seems to be confusion on what it will look like. Google literally told us. Let me clarify for anyone who is still unsure of what is rolling out this week. Last month Google responded to everyone saying Search is dead. Here is what they said: "You will absolutely continue to see blue web links in search results. AI Mode is not the default experience in Search. You will continue to get a range of results on Search." [Want to know where your site stands across Google AI, ChatGPT, Claude, Grok, etc? Check here (it's free): Google has explicitly laid out what Search will look like from this point going forward. The new Search box accepts text, images, files, videos, and open Chrome tabs. It anticipates your intent before you finish asking. It is powered by the most advanced Gemini model Google has ever put into Search, and layered on top of that, information agents will now be able to run 24/7 in the background on behalf of your buyer. Think of it in 5 steps: Step 1: The buyer describes their problem, their category, their needs in full. Step 2: The agent breaks that down into sub-topics and maps out a plan. Step 3: It determines what intel is needed right now versus later. Step 4: It monitors blogs, news sites, and social posts continuously for relevant changes. Step 5: It sends the buyer a synthesized update with links and the ability to take action. Blue links are not going away in the short-term, but the brands getting recommended by information agents 24 hours a day while also ranking in traditional results are going to pull so far ahead of the ones doing only one or the other that it will not be a fair fight. This is exactly what SEO Stuff ( has been building for every customer. Optimized content depth that covers every sub-question a buyer in your category asks, so the agent finds you at every step of its plan. Editorial authority from trusted websites that signals credibility to every retrieval system Google has ever built, across both traditional rankings and AI citations simultaneously. One investment. Blue links and AI citations. Around the clock. SEO Stuff's Complete Done-For-You Plan: SEO Stuff's "Optimized Content" Plan: There is a reason more than 80 percent of SEO Stuff customers reorder. The results continue long after the work is done. Google Search is changing. AI Search is here. Your websites need to prepare accordingly. Want to know where your site stands across Google AI, ChatGPT, Claude, Grok, etc? Check here (it's free):

The new Google Search is rolling out and there seems to be confusion on what it will look like. Google literally told us. Let me clarify for anyone who is still unsure of what is rolling out this week. Last month Google responded to everyone saying Search is dead. Here is what they said: "You will absolutely continue to see blue web links in search results. AI Mode is not the default experience in Search. You will continue to get a range of results on Search." [Want to know where your site stands across Google AI, ChatGPT, Claude, Grok, etc? Check here (it's free): Google has explicitly laid out what Search will look like from this point going forward. The new Search box accepts text, images, files, videos, and open Chrome tabs. It anticipates your intent before you finish asking. It is powered by the most advanced Gemini model Google has ever put into Search, and layered on top of that, information agents will now be able to run 24/7 in the background on behalf of your buyer. Think of it in 5 steps: Step 1: The buyer describes their problem, their category, their needs in full. Step 2: The agent breaks that down into sub-topics and maps out a plan. Step 3: It determines what intel is needed right now versus later. Step 4: It monitors blogs, news sites, and social posts continuously for relevant changes. Step 5: It sends the buyer a synthesized update with links and the ability to take action. Blue links are not going away in the short-term, but the brands getting recommended by information agents 24 hours a day while also ranking in traditional results are going to pull so far ahead of the ones doing only one or the other that it will not be a fair fight. This is exactly what SEO Stuff ( has been building for every customer. Optimized content depth that covers every sub-question a buyer in your category asks, so the agent finds you at every step of its plan. Editorial authority from trusted websites that signals credibility to every retrieval system Google has ever built, across both traditional rankings and AI citations simultaneously. One investment. Blue links and AI citations. Around the clock. SEO Stuff's Complete Done-For-You Plan: SEO Stuff's "Optimized Content" Plan: There is a reason more than 80 percent of SEO Stuff customers reorder. The results continue long after the work is done. Google Search is changing. AI Search is here. Your websites need to prepare accordingly. Want to know where your site stands across Google AI, ChatGPT, Claude, Grok, etc? Check here (it's free):

Alex Groberman

44,078 views • 2 months ago

The new Google Search is rolling out and there seems to be confusion on what it will look like. Google literally showed us. Let me clarify for anyone who is still unsure of what is rolling out right now. Last month Google responded to everyone saying Search is dead. Here is what they said: "You will absolutely continue to see blue web links in search results. AI Mode is not the default experience in Search. You will continue to get a range of results on Search." [Want to know where your site stands across Google AI, ChatGPT, Claude, Grok, etc? Check here (it's free): Google has explicitly laid out what Search will look like from this point going forward. The new Search box accepts text, images, files, videos, and open Chrome tabs. It anticipates your intent before you finish asking. It is powered by the most advanced Gemini model Google has ever put into Search, and layered on top of that, information agents will now be able to run 24/7 in the background on behalf of your buyer. Think of it in 5 steps: Step 1: The buyer describes their problem, their category, their needs in full. Step 2: The agent breaks that down into sub-topics and maps out a plan. Step 3: It determines what intel is needed right now versus later. Step 4: It monitors blogs, news sites, and social posts continuously for relevant changes. Step 5: It sends the buyer a synthesized update with links and the ability to take action. Blue links are not going away in the short-term, but the brands getting recommended by information agents 24 hours a day while also ranking in traditional results are going to pull so far ahead of the ones doing only one or the other that it will not be a fair fight. This is exactly what SEO Stuff ( has been building for every customer. Optimized content depth that covers every sub-question a buyer in your category asks, so the agent finds you at every step of its plan. Editorial authority from trusted websites that signals credibility to every retrieval system Google has ever built, across both traditional rankings and AI citations simultaneously. One investment. Blue links and AI citations. Around the clock. SEO Stuff's Complete Done-For-You Plan: SEO Stuff's "Optimized Content" Plan: There is a reason more than 80 percent of SEO Stuff customers reorder. The results continue long after the work is done. Google Search is changing. AI Search is here. Your websites need to prepare accordingly. Want to know where your site stands across Google AI, ChatGPT, Claude, Grok, etc? Check here (it's free):

The new Google Search is rolling out and there seems to be confusion on what it will look like. Google literally showed us. Let me clarify for anyone who is still unsure of what is rolling out right now. Last month Google responded to everyone saying Search is dead. Here is what they said: "You will absolutely continue to see blue web links in search results. AI Mode is not the default experience in Search. You will continue to get a range of results on Search." [Want to know where your site stands across Google AI, ChatGPT, Claude, Grok, etc? Check here (it's free): Google has explicitly laid out what Search will look like from this point going forward. The new Search box accepts text, images, files, videos, and open Chrome tabs. It anticipates your intent before you finish asking. It is powered by the most advanced Gemini model Google has ever put into Search, and layered on top of that, information agents will now be able to run 24/7 in the background on behalf of your buyer. Think of it in 5 steps: Step 1: The buyer describes their problem, their category, their needs in full. Step 2: The agent breaks that down into sub-topics and maps out a plan. Step 3: It determines what intel is needed right now versus later. Step 4: It monitors blogs, news sites, and social posts continuously for relevant changes. Step 5: It sends the buyer a synthesized update with links and the ability to take action. Blue links are not going away in the short-term, but the brands getting recommended by information agents 24 hours a day while also ranking in traditional results are going to pull so far ahead of the ones doing only one or the other that it will not be a fair fight. This is exactly what SEO Stuff ( has been building for every customer. Optimized content depth that covers every sub-question a buyer in your category asks, so the agent finds you at every step of its plan. Editorial authority from trusted websites that signals credibility to every retrieval system Google has ever built, across both traditional rankings and AI citations simultaneously. One investment. Blue links and AI citations. Around the clock. SEO Stuff's Complete Done-For-You Plan: SEO Stuff's "Optimized Content" Plan: There is a reason more than 80 percent of SEO Stuff customers reorder. The results continue long after the work is done. Google Search is changing. AI Search is here. Your websites need to prepare accordingly. Want to know where your site stands across Google AI, ChatGPT, Claude, Grok, etc? Check here (it's free):

Alex Groberman

23,380 views • 20 days ago

10 free Google AI tools nobody talks about. while everyone's burning $20/mo on chatgpt and claude, google quietly shipped a stack worth $200+/mo. all free. all yours. — 1️⃣ NotebookLM — your second brain upload sources (PDFs, websites, audio, YouTube). it summarizes, builds mind maps, generates quizzes, drafts slide decks, even turns your notes into a podcast you can listen to on a walk. free tier: 100 notebooks, 50 sources each, 50 chats/day, 3 audio overviews/day. replaces: notion AI + perplexity + readwise — 2️⃣ Google AI Studio — the free gemini playground web playground for gemini 3 pro and flash with a free API key. generous limits. paste a 1M-token context window and watch it actually use it. faster than the openai playground and free where openai charges per token. replaces: openai playground + paid API credits — 3️⃣ Gemini CLI — google's open-source terminal agent apache 2.0 licensed. one command (npx @google/gemini-cli) and you've got an agent in your terminal that reads your codebase, runs shell commands, and ships PRs. drop-in claude code alternative. replaces: claude code ($20/mo by default) — 4️⃣ Jules — async coding agent assign jules a github issue. it spins up a cloud VM, clones your repo, writes the plan, makes the changes, opens a PR. free tier: 15 tasks/day, 3 concurrent, runs on gemini flash. replaces: devin ($20/mo+) + cursor agent 5️⃣ Stitch — text → UI → code google's free figma killer. describe an interface, get production-ready HTML/CSS/Tailwind + figma export. march 2026 update added voice canvas, infinite canvas, and MCP integration with cursor. 350 standard + 200 experimental generations/month free. replaces: galileo AI + early-stage figma work — 6️⃣ Gemma 4 — open-weight LLM google's flagship open model. apache 2.0. 2B, 4B, 26B-MoE, and 31B variants. 256K context. runs on ollama with one command. quantized versions run on a 4090 or beefy laptop. replaces: paying for hosted LLM inference — 7️⃣ Illuminate — papers → podcasts paste an arxiv preprint link. illuminate turns dense research papers into a 6-8 min conversation between two AI hosts breaking it down. perfect for commute reading you can't do at a desk. note: still in waitlist for some regions. replaces: snipd + manual research reading — 8️⃣ Learn About (LearnLM) — adaptive AI tutor drop in any topic you're stuck on. highlight a word, click "go deeper," and the interface adapts in real time to your comprehension level. visual explanations, follow-up questions, the works. replaces: paid tutoring on niche topics — 9️⃣ Google Labs FX (ImageFX + Flow + MusicFX) — free imagen, veo, musicLM google labs creative suite. text-to-image (imagen 4), text-to-video (veo via Flow), text-to-music (musicLM). free tier: limited daily generations. the heavy veo 3.1 features are paid (AI Pro $19.99/mo). still worth using for image and music — those stay free. replaces: midjourney + suno (free tier only — runway-level video gen is paid) — 🔟 Google Colab — free GPU notebooks free T4 GPU + 12GB RAM in a browser tab. enough to fine-tune small models, run stable diffusion, prototype agents. the launching pad for half the ML projects on github. replaces: paid cloud GPU rentals — a quick honest note: these tools aren't 1:1 better than the paid versions they replace. but they're decent enough to get most things done — especially if you're not a heavy user or you've got little funds to play with. i've put all 10 in a public github repo (link in comments). follow + turn on post notifications for more useful posts like this 🔔

10 free Google AI tools nobody talks about. while everyone's burning $20/mo on chatgpt and claude, google quietly shipped a stack worth $200+/mo. all free. all yours. — 1️⃣ NotebookLM — your second brain upload sources (PDFs, websites, audio, YouTube). it summarizes, builds mind maps, generates quizzes, drafts slide decks, even turns your notes into a podcast you can listen to on a walk. free tier: 100 notebooks, 50 sources each, 50 chats/day, 3 audio overviews/day. replaces: notion AI + perplexity + readwise — 2️⃣ Google AI Studio — the free gemini playground web playground for gemini 3 pro and flash with a free API key. generous limits. paste a 1M-token context window and watch it actually use it. faster than the openai playground and free where openai charges per token. replaces: openai playground + paid API credits — 3️⃣ Gemini CLI — google's open-source terminal agent apache 2.0 licensed. one command (npx @google/gemini-cli) and you've got an agent in your terminal that reads your codebase, runs shell commands, and ships PRs. drop-in claude code alternative. replaces: claude code ($20/mo by default) — 4️⃣ Jules — async coding agent assign jules a github issue. it spins up a cloud VM, clones your repo, writes the plan, makes the changes, opens a PR. free tier: 15 tasks/day, 3 concurrent, runs on gemini flash. replaces: devin ($20/mo+) + cursor agent 5️⃣ Stitch — text → UI → code google's free figma killer. describe an interface, get production-ready HTML/CSS/Tailwind + figma export. march 2026 update added voice canvas, infinite canvas, and MCP integration with cursor. 350 standard + 200 experimental generations/month free. replaces: galileo AI + early-stage figma work — 6️⃣ Gemma 4 — open-weight LLM google's flagship open model. apache 2.0. 2B, 4B, 26B-MoE, and 31B variants. 256K context. runs on ollama with one command. quantized versions run on a 4090 or beefy laptop. replaces: paying for hosted LLM inference — 7️⃣ Illuminate — papers → podcasts paste an arxiv preprint link. illuminate turns dense research papers into a 6-8 min conversation between two AI hosts breaking it down. perfect for commute reading you can't do at a desk. note: still in waitlist for some regions. replaces: snipd + manual research reading — 8️⃣ Learn About (LearnLM) — adaptive AI tutor drop in any topic you're stuck on. highlight a word, click "go deeper," and the interface adapts in real time to your comprehension level. visual explanations, follow-up questions, the works. replaces: paid tutoring on niche topics — 9️⃣ Google Labs FX (ImageFX + Flow + MusicFX) — free imagen, veo, musicLM google labs creative suite. text-to-image (imagen 4), text-to-video (veo via Flow), text-to-music (musicLM). free tier: limited daily generations. the heavy veo 3.1 features are paid (AI Pro $19.99/mo). still worth using for image and music — those stay free. replaces: midjourney + suno (free tier only — runway-level video gen is paid) — 🔟 Google Colab — free GPU notebooks free T4 GPU + 12GB RAM in a browser tab. enough to fine-tune small models, run stable diffusion, prototype agents. the launching pad for half the ML projects on github. replaces: paid cloud GPU rentals — a quick honest note: these tools aren't 1:1 better than the paid versions they replace. but they're decent enough to get most things done — especially if you're not a heavy user or you've got little funds to play with. i've put all 10 in a public github repo (link in comments). follow + turn on post notifications for more useful posts like this 🔔

m0h

11,847 views • 2 months ago

Y Combinator CEO, Garry Tan, took the stage for 42 minutes at Startup School 2026 and explained how to build your own personal AGI better than any paid AI course. This is what he told the room: 1. The leverage is in your context, not the model. Tan watches hundreds of founders use identical models every batch. "There are 2x people and there are 100x people who are using the same Claude. Same weights, same context window size, same API. But the leverage is not in the weights." The gap between users is now bigger than the gap between models. 2. One person's output went up 400x. In 2013 Tan shipped maybe 14 useful lines of code a day as a YC partner, dead on the median for programmer productivity. "I did the math on my output, and I'm at about 400x what I did in 2013." 3. Agents run on a different working memory. Humans hold 7 things in their head at once. Every org chart and checklist ever built is a patch for that limit. "An AI agent holds a million tokens. That's about a thousand pages. Three Harry Potter books sitting open on its head all at once." You're still running your week on tools built for the 7-digit brain. 4. Markdown is code now. Tan's stack is mostly skill files: pages of plain English an agent can execute. "If you can write clear instructions in English, you're a programmer. The compiler is a language model." At YC, finance and events staff who never opened a terminal are building automations. 5. Your history is your moat. Tan's agent runs on a personal wiki: about 220,000 markdown pages covering 25 years of email, meetings, notes and decisions. "When my agent does anything, it does knowing everything I know. And that's the difference between an assistant and a colleague." No frontier model has your context. That's the one asset nobody can replicate. 6. Never do one-off work. Most people run a task with an agent, close the window and throw the learning away. Tan ends every task by having the agent turn what it did into a reusable skill file. "If you have to ask for something twice, you failed." Captured skills compound daily. Amnesia resets you to zero every morning. 7. Own your skill files before your employer does. A skill file is your judgment, extracted and executable. The only question is who controls it. "Own your skills because if you don't, your job becomes a skill file." Files in your repo compound your career. Files in the company's repo run your judgment without you. Watch it, then read the step-by-step guide on becoming an AI engineer.

Y Combinator CEO, Garry Tan, took the stage for 42 minutes at Startup School 2026 and explained how to build your own personal AGI better than any paid AI course. This is what he told the room: 1. The leverage is in your context, not the model. Tan watches hundreds of founders use identical models every batch. "There are 2x people and there are 100x people who are using the same Claude. Same weights, same context window size, same API. But the leverage is not in the weights." The gap between users is now bigger than the gap between models. 2. One person's output went up 400x. In 2013 Tan shipped maybe 14 useful lines of code a day as a YC partner, dead on the median for programmer productivity. "I did the math on my output, and I'm at about 400x what I did in 2013." 3. Agents run on a different working memory. Humans hold 7 things in their head at once. Every org chart and checklist ever built is a patch for that limit. "An AI agent holds a million tokens. That's about a thousand pages. Three Harry Potter books sitting open on its head all at once." You're still running your week on tools built for the 7-digit brain. 4. Markdown is code now. Tan's stack is mostly skill files: pages of plain English an agent can execute. "If you can write clear instructions in English, you're a programmer. The compiler is a language model." At YC, finance and events staff who never opened a terminal are building automations. 5. Your history is your moat. Tan's agent runs on a personal wiki: about 220,000 markdown pages covering 25 years of email, meetings, notes and decisions. "When my agent does anything, it does knowing everything I know. And that's the difference between an assistant and a colleague." No frontier model has your context. That's the one asset nobody can replicate. 6. Never do one-off work. Most people run a task with an agent, close the window and throw the learning away. Tan ends every task by having the agent turn what it did into a reusable skill file. "If you have to ask for something twice, you failed." Captured skills compound daily. Amnesia resets you to zero every morning. 7. Own your skill files before your employer does. A skill file is your judgment, extracted and executable. The only question is who controls it. "Own your skills because if you don't, your job becomes a skill file." Files in your repo compound your career. Files in the company's repo run your judgment without you. Watch it, then read the step-by-step guide on becoming an AI engineer.

Alex Prompter

246,164 views • 10 days ago

This is the first real AI cold war. Anthropic is HIDING secret spy code inside its most popular coding tool. The code was designed to identify Chinese users without their knowledge. Now Alibaba has banned every single Anthropic product from its entire company. And the full picture is way more insane than either side wants you to see: On June 30, a security researcher on Reddit reverse-engineered Claude Code, Anthropic's AI coding agent that has deep access to every file on your computer. What they found buried inside the software was genuinely disturbing... Since April 2, Anthropic had been silently shipping hidden detection code inside every copy of Claude Code. The code checked whether your system timezone was set to Shanghai or Urumqi. It scanned your proxy settings against a hardcoded list of Chinese corporate networks, specifically targeting Alibaba, ByteDance, Baidu, and Moonshot AI. But here is the part that made security researchers lose their minds: The code did not send a normal signal back to Anthropic's servers. Instead it used steganography, a technique from military intelligence, to hide its findings INSIDE the text Claude was already generating. It swapped invisible Unicode characters in Claude's system prompt. Changed a standard apostrophe to one of three visually identical but technically different characters depending on which flags triggered. Switched date formats from dashes to slashes. Invisible to the human eye. But perfectly readable by Anthropic's backend. The detection logic was XOR-obfuscated to prevent anyone from finding it during a code review. It shipped with zero disclosure in the release notes. Three months of silent surveillance baked into a tool that has full access to your local file system. An Anthropic engineer confirmed the whole thing on X on July 2. Called it "an experiment we launched in March that was meant to prevent account abuse." Said the team had "been meaning to take this down for a while." The code was removed on July 1, one day after the Reddit post went viral. Three months of covert user fingerprinting. Removed the day after someone found it. Described as an experiment they forgot to turn off... Now here is where it becomes a full blown corporate war: Three weeks before the backdoor was discovered, Anthropic had sent a letter to the US Senate Banking Committee accusing operators linked to Alibaba's Qwen AI lab of running the largest model theft campaign in the company's history. 25,000 fake accounts. 28.8 million queries over 44 days. All designed to copy Claude's reasoning capabilities and train a competing Chinese model for free. So the sequence reads like this: Alibaba allegedly steals Claude's brain using 25,000 fake accounts. Anthropic responds by secretly embedding surveillance code inside Claude Code to catch them. A Reddit user catches Anthropic doing it. Alibaba uses the discovery as justification to ban every Anthropic product from its entire workforce effective July 10 and force 200,000 employees onto its own tool, Qoder. The thief caught the cop planting a wiretap. And now the thief is using the wiretap as evidence that the cop is the real criminal. Alibaba classified Claude Code as "high-risk software with security vulnerabilities" in an internal notice reported by the South China Morning Post. Meanwhile Anthropic is simultaneously fighting the Pentagon over a blacklist designation, lobbying Washington to crack down on Chinese distillation, and getting caught running the exact kind of covert operation that makes their "responsible AI" branding look like a punchline. Alibaba allegedly ran the largest AI theft operation ever documented. Anthropic secretly built invisible tracking into a tool with root access to your computer. The US government restricted American access to the very models China already copied. And a random Reddit user with a debugger exposed the whole thing.

This is the first real AI cold war. Anthropic is HIDING secret spy code inside its most popular coding tool. The code was designed to identify Chinese users without their knowledge. Now Alibaba has banned every single Anthropic product from its entire company. And the full picture is way more insane than either side wants you to see: On June 30, a security researcher on Reddit reverse-engineered Claude Code, Anthropic's AI coding agent that has deep access to every file on your computer. What they found buried inside the software was genuinely disturbing... Since April 2, Anthropic had been silently shipping hidden detection code inside every copy of Claude Code. The code checked whether your system timezone was set to Shanghai or Urumqi. It scanned your proxy settings against a hardcoded list of Chinese corporate networks, specifically targeting Alibaba, ByteDance, Baidu, and Moonshot AI. But here is the part that made security researchers lose their minds: The code did not send a normal signal back to Anthropic's servers. Instead it used steganography, a technique from military intelligence, to hide its findings INSIDE the text Claude was already generating. It swapped invisible Unicode characters in Claude's system prompt. Changed a standard apostrophe to one of three visually identical but technically different characters depending on which flags triggered. Switched date formats from dashes to slashes. Invisible to the human eye. But perfectly readable by Anthropic's backend. The detection logic was XOR-obfuscated to prevent anyone from finding it during a code review. It shipped with zero disclosure in the release notes. Three months of silent surveillance baked into a tool that has full access to your local file system. An Anthropic engineer confirmed the whole thing on X on July 2. Called it "an experiment we launched in March that was meant to prevent account abuse." Said the team had "been meaning to take this down for a while." The code was removed on July 1, one day after the Reddit post went viral. Three months of covert user fingerprinting. Removed the day after someone found it. Described as an experiment they forgot to turn off... Now here is where it becomes a full blown corporate war: Three weeks before the backdoor was discovered, Anthropic had sent a letter to the US Senate Banking Committee accusing operators linked to Alibaba's Qwen AI lab of running the largest model theft campaign in the company's history. 25,000 fake accounts. 28.8 million queries over 44 days. All designed to copy Claude's reasoning capabilities and train a competing Chinese model for free. So the sequence reads like this: Alibaba allegedly steals Claude's brain using 25,000 fake accounts. Anthropic responds by secretly embedding surveillance code inside Claude Code to catch them. A Reddit user catches Anthropic doing it. Alibaba uses the discovery as justification to ban every Anthropic product from its entire workforce effective July 10 and force 200,000 employees onto its own tool, Qoder. The thief caught the cop planting a wiretap. And now the thief is using the wiretap as evidence that the cop is the real criminal. Alibaba classified Claude Code as "high-risk software with security vulnerabilities" in an internal notice reported by the South China Morning Post. Meanwhile Anthropic is simultaneously fighting the Pentagon over a blacklist designation, lobbying Washington to crack down on Chinese distillation, and getting caught running the exact kind of covert operation that makes their "responsible AI" branding look like a punchline. Alibaba allegedly ran the largest AI theft operation ever documented. Anthropic secretly built invisible tracking into a tool with root access to your computer. The US government restricted American access to the very models China already copied. And a random Reddit user with a debugger exposed the whole thing.

Ricardo

23,634 views • 1 month ago

MEET THE NVIDIA KILLER: OpenAI bet $10 BILLION on this company that makes chips 20x faster than Nvidia's. If this plays out as expected, it’s over for Nvidia. Cerebras Systems just locked in 750 megawatts of computing power to OpenAI through 2028. For reference: that's equivalent to the annual power consumption of 600,000 US homes. The deal? Over $10 billion. Here's what nobody understands: Cerebras doesn't make normal chips. Nvidia sells you thousands of tiny chips that you connect together. Cerebras makes ONE chip. A single wafer-scale processor the size of a dinner plate. 900,000 AI cores. 4 trillion transistors. All on one piece of silicon. The result? When OpenAI tested it, Cerebras ran inference 20X FASTER than Nvidia GPUs. That's not incremental improvement. That's a different category of performance. But here's where the story gets wild: Four months ago, Cerebras was a struggling company. Their IPO filing revealed that 87% of their revenue came from ONE customer: G42, a UAE-based AI firm. The US government launched a national security review. G42 had ties to Huawei. Ties to China. The IPO collapsed. Investors panicked. Cerebras withdrew their filing in October 2025. Most startups would've been dead. Instead, Cerebras did the opposite. They raised $1.1 billion at an $8.1 billion valuation. Kicked G42 out of the cap table entirely. Got CFIUS clearance. Then landed the OpenAI deal. Now they're raising ANOTHER $1 billion at a $22 billion valuation. They more than DOUBLED their valuation in 4 months. From near-death to $22 billion. While getting rid of their biggest customer. Why OpenAI chose them: ChatGPT has 900 million weekly users. Sam Altman keeps saying they have a "severe shortage" of compute. They need SPEED, not just power. When you ask ChatGPT a question, there's a loop happening: You send request → model thinks → sends response back Nvidia chips are fast at training models. Cerebras chips are built specifically for inference. For real-time responses. For the exact bottleneck OpenAI is trying to solve. Sachin Katti from OpenAI said it best: "Cerebras adds a dedicated low-latency inference solution to our platform. That means faster responses, more natural interactions, and a stronger foundation to scale real-time AI to many more people." In other words: "We need this to scale ChatGPT." The competitive landscape just shifted: Nvidia announced a $100 billion deal with OpenAI in September. But it's still not finalized. Meanwhile, Cerebras closed their deal before Thanksgiving. And it's ALREADY being deployed. Here's the part that should terrify Nvidia: In December, Nvidia bought Groq for $20 billion. Groq makes fast inference chips. Just like Cerebras. So why would Nvidia spend $20 billion buying a competitor to something they supposedly already dominate? Because they know what's coming. Inference is the new battleground. And Cerebras is winning it. The IPO is coming Q2 2026. After this OpenAI deal, Cerebras now has: ✓ IBM contracts ✓ Department of Energy contracts ✓ OpenAI locked in for 3 years ✓ $22 billion valuation ✓ CFIUS clearance ✓ Zero customer concentration risk They went from 87% revenue dependency on one customer to the most diversified chip company outside Nvidia. In four months. The lesson? Smart money doesn't follow headlines. It follows where the AI leaders are actually spending. OpenAI didn't announce this deal for publicity. They need Cerebras hardware to scale ChatGPT. That's a $10 billion vote of confidence. While everyone's watching Nvidia stock, the real war is happening in inference. And the company with ONE giant chip just beat the company with thousands of tiny ones. What do you think happens when Cerebras IPOs?

MEET THE NVIDIA KILLER: OpenAI bet $10 BILLION on this company that makes chips 20x faster than Nvidia's. If this plays out as expected, it’s over for Nvidia. Cerebras Systems just locked in 750 megawatts of computing power to OpenAI through 2028. For reference: that's equivalent to the annual power consumption of 600,000 US homes. The deal? Over $10 billion. Here's what nobody understands: Cerebras doesn't make normal chips. Nvidia sells you thousands of tiny chips that you connect together. Cerebras makes ONE chip. A single wafer-scale processor the size of a dinner plate. 900,000 AI cores. 4 trillion transistors. All on one piece of silicon. The result? When OpenAI tested it, Cerebras ran inference 20X FASTER than Nvidia GPUs. That's not incremental improvement. That's a different category of performance. But here's where the story gets wild: Four months ago, Cerebras was a struggling company. Their IPO filing revealed that 87% of their revenue came from ONE customer: G42, a UAE-based AI firm. The US government launched a national security review. G42 had ties to Huawei. Ties to China. The IPO collapsed. Investors panicked. Cerebras withdrew their filing in October 2025. Most startups would've been dead. Instead, Cerebras did the opposite. They raised $1.1 billion at an $8.1 billion valuation. Kicked G42 out of the cap table entirely. Got CFIUS clearance. Then landed the OpenAI deal. Now they're raising ANOTHER $1 billion at a $22 billion valuation. They more than DOUBLED their valuation in 4 months. From near-death to $22 billion. While getting rid of their biggest customer. Why OpenAI chose them: ChatGPT has 900 million weekly users. Sam Altman keeps saying they have a "severe shortage" of compute. They need SPEED, not just power. When you ask ChatGPT a question, there's a loop happening: You send request → model thinks → sends response back Nvidia chips are fast at training models. Cerebras chips are built specifically for inference. For real-time responses. For the exact bottleneck OpenAI is trying to solve. Sachin Katti from OpenAI said it best: "Cerebras adds a dedicated low-latency inference solution to our platform. That means faster responses, more natural interactions, and a stronger foundation to scale real-time AI to many more people." In other words: "We need this to scale ChatGPT." The competitive landscape just shifted: Nvidia announced a $100 billion deal with OpenAI in September. But it's still not finalized. Meanwhile, Cerebras closed their deal before Thanksgiving. And it's ALREADY being deployed. Here's the part that should terrify Nvidia: In December, Nvidia bought Groq for $20 billion. Groq makes fast inference chips. Just like Cerebras. So why would Nvidia spend $20 billion buying a competitor to something they supposedly already dominate? Because they know what's coming. Inference is the new battleground. And Cerebras is winning it. The IPO is coming Q2 2026. After this OpenAI deal, Cerebras now has: ✓ IBM contracts ✓ Department of Energy contracts ✓ OpenAI locked in for 3 years ✓ $22 billion valuation ✓ CFIUS clearance ✓ Zero customer concentration risk They went from 87% revenue dependency on one customer to the most diversified chip company outside Nvidia. In four months. The lesson? Smart money doesn't follow headlines. It follows where the AI leaders are actually spending. OpenAI didn't announce this deal for publicity. They need Cerebras hardware to scale ChatGPT. That's a $10 billion vote of confidence. While everyone's watching Nvidia stock, the real war is happening in inference. And the company with ONE giant chip just beat the company with thousands of tiny ones. What do you think happens when Cerebras IPOs?

Ricardo

28,088 views • 7 months ago

Perplexity declared war on the biggest open source AI movement of 2026. This changes how millions of people will interact with AI agents forever. Here is what happened and why almost nobody is talking about the real implications. OpenClaw exploded in January and it became one of the fastest growing open source projects in GitHub history. The premise was radical. An AI agent that runs on your own machine, connects to your messaging apps and actually does things while you sleep. Developers went wild and over 700 community built skills appeared on ClawHub. People were negotiating car deals, filing legal rebuttals, and building entire social networks run by AI agents. Then Perplexity showed up with something different. A cloud powered system that coordinates 20 frontier AI models at once. They call it Perplexity Computer and this week they went even further. They announced Personal Computer. An always on AI agent that lives on a Mac mini in your home, connected to your local files and Perplexity's secure servers around the clock. It never sleeps or stops working and you control it from any device, anywhere. But the real story is what CEO Aravind Srinivas said during the Q&A session at their inaugural developer conference in San Francisco. He called Perplexity Computer a product "meant for serious people." He talked about Uber drivers asking him when they could stop driving and let AI make them passive income. That, he said, is the actual vision and then he went directly after OpenClaw. He said even a former Perplexity engineer struggled to get OpenClaw running on their own machine. He warned about unvetted malware being imported through OpenClaw's community skill hub, with no control over what people are contributing. He called the hobbyist approach of managing 700 API keys and sub agent configuration files a dead end for mainstream adoption. And four years of building world class orchestration gives Perplexity something an open source project cannot match. Enterprise grade security for solopreneurs and businesses alike. On one side, OpenClaw represents radical openness. Your data stays local, you choose your own models, you own everything and the community builds the tools. On the other hand, Perplexity is betting that most people don’t want to be system administrators. They want results, security guarantees, and something that just works out of the box. The Personal Computer runs on Perplexity's SOC 2 certified infrastructure. Every sensitive action requires user approval, every action is logged, and there is a kill switch. The enterprise version connects natively to Snowflake, Salesforce, HubSpot, and hundreds of other platforms. Teams can query data warehouses and build financial models without waiting on an analytics team. The real question is not which product is technically better. The real question is whether the future of AI agents looks like Linux or looks like the iPhone. Because the Uber driver Srinivas described is not going to configure sub agent routing tables. That person needs something that works the moment they open it. And if Perplexity captures that market, the open source movement becomes a niche for developers instead of a revolution for everyone. That is the billion dollar bet being made right now.

Perplexity declared war on the biggest open source AI movement of 2026. This changes how millions of people will interact with AI agents forever. Here is what happened and why almost nobody is talking about the real implications. OpenClaw exploded in January and it became one of the fastest growing open source projects in GitHub history. The premise was radical. An AI agent that runs on your own machine, connects to your messaging apps and actually does things while you sleep. Developers went wild and over 700 community built skills appeared on ClawHub. People were negotiating car deals, filing legal rebuttals, and building entire social networks run by AI agents. Then Perplexity showed up with something different. A cloud powered system that coordinates 20 frontier AI models at once. They call it Perplexity Computer and this week they went even further. They announced Personal Computer. An always on AI agent that lives on a Mac mini in your home, connected to your local files and Perplexity's secure servers around the clock. It never sleeps or stops working and you control it from any device, anywhere. But the real story is what CEO Aravind Srinivas said during the Q&A session at their inaugural developer conference in San Francisco. He called Perplexity Computer a product "meant for serious people." He talked about Uber drivers asking him when they could stop driving and let AI make them passive income. That, he said, is the actual vision and then he went directly after OpenClaw. He said even a former Perplexity engineer struggled to get OpenClaw running on their own machine. He warned about unvetted malware being imported through OpenClaw's community skill hub, with no control over what people are contributing. He called the hobbyist approach of managing 700 API keys and sub agent configuration files a dead end for mainstream adoption. And four years of building world class orchestration gives Perplexity something an open source project cannot match. Enterprise grade security for solopreneurs and businesses alike. On one side, OpenClaw represents radical openness. Your data stays local, you choose your own models, you own everything and the community builds the tools. On the other hand, Perplexity is betting that most people don’t want to be system administrators. They want results, security guarantees, and something that just works out of the box. The Personal Computer runs on Perplexity's SOC 2 certified infrastructure. Every sensitive action requires user approval, every action is logged, and there is a kill switch. The enterprise version connects natively to Snowflake, Salesforce, HubSpot, and hundreds of other platforms. Teams can query data warehouses and build financial models without waiting on an analytics team. The real question is not which product is technically better. The real question is whether the future of AI agents looks like Linux or looks like the iPhone. Because the Uber driver Srinivas described is not going to configure sub agent routing tables. That person needs something that works the moment they open it. And if Perplexity captures that market, the open source movement becomes a niche for developers instead of a revolution for everyone. That is the billion dollar bet being made right now.

Milk Road AI

22,256 views • 5 months ago

I can't believe that the once richest man on earth just bet his entire empire on ONE company. And he has 9 days to pull it off. SoftBank is scrambling to deliver $22.5 billion to OpenAI by December 31st. To get there, CEO Masayoshi Son sold his ENTIRE stake in the best-performing AI stock on the planet. Then sold billions more in other holdings. Cut staff. Froze dealmaking. Borrowed against everything he owns. This is the biggest all-in bet in the past few years. And it might be the most reckless financial engineering since 2008. Here's what's actually happening: SoftBank promised OpenAI $40 billion back in April when the company was valued at $300 billion. The deal had conditions. OpenAI had to convert to a for-profit structure by year-end. They did that in October. Now the clock is ticking. $22.5 billion must arrive in 9 days or the deal breaks. Son already delivered $17.5 billion earlier this year. Getting the rest is proving harder than anyone expected. The moves Son made to raise the cash are absolutely wild: He dumped SoftBank's entire $5.8 billion position in Nvidia. Not trimmed. Not reduced. LIQUIDATED. The same Nvidia that's been printing money for AI investors all year. He sold $4.8 billion worth of T-Mobile shares. Slashed staff across the company. And the Vision Fund that used to write checks for everything? Dead. Any deal over $50 million now requires Son's personal approval. Investment managers who used to hunt for the next big thing are now working full-time on the OpenAI transaction. But it still wasn't enough cash... So Son went to the debt markets. He expanded SoftBank's margin loan capacity by $6.5 billion, bringing total undrawn capacity to $11.5 billion. All of it backed by Arm Holdings stock. If Arm's stock drops, those loans get called. SoftBank faces margin calls. The whole thing unravels. And the risk gets crazier. OpenAI's valuation has tripled since April. Started at $300 billion. Now heading toward $900 billion according to sources. Amazon is reportedly joining the next round. On paper, SoftBank's investment looks brilliant. A 3X return in 8 months. But here's the thing: OpenAI is hemorrhaging cash at a rate that makes Uber's losses look responsible. The company generates $13 billion in annual revenue. Impressive... right? But they're literally projected to LOSE $74 billion by 2028. Not break even with losses. Not approach profitability. $74 billion in the red. Their revenue is growing. Their losses are growing faster. Because AI compute costs don't scale down. They scale UP. Every new ChatGPT user costs OpenAI money. Every API call burns cash. Every model training run requires millions in compute. Sam Altman told employees OpenAI is now in "code red" mode. Pausing all other product launches to focus entirely on beating Google's Gemini. That's the language of desperation. And Altman's long-term vision is even more expensive. He wants to build 30 gigawatts of AI compute capacity. Cost: $1.4 TRILLION. For context, that's larger than Mexico's entire GDP. He wants to add 1 gigawat every single week. Each gigawatt costs over $40 billion. The math doesn't work. The business model doesn't work. The capital requirements are impossible. But Son is betting everything anyway. Why would he do this? Because if it works, he owns the future. If OpenAI becomes the infrastructure layer for the next 20 years of computing, that $22.5 billion turns into trillions. SoftBank becomes the kingmaker of AI. Son becomes the most powerful investor in history. But if it fails? SoftBank vaporizes. The Nvidia stake is gone. Can't get it back. The T-Mobile shares are gone. The margin loans against Arm come due. Son has systematically dismantled his portfolio to concentrate everything into one bet. This is the opposite of diversification. This is the opposite of prudent risk management. This is a founder going all-in on a vision that everyone else thinks is insane. And he might be right. Other investors see it too. That's why OpenAI's valuation tripled in 8 months. BlackRock, Fidelity, and JP Morgan are all writing massive checks to private AI companies. Databricks just raised $4 billion at a $134 billion valuation. The entire market is betting that AI infrastructure will define the next decade. But the difference? They're diversifying. Spreading risk. Building portfolios. Son put everything on one company. The deadline is December 31st. In 9 days, we'll know if SoftBank pulled it off. If they deliver the $22.5 billion on time, the bet stays alive. If they miss the deadline, the deal could collapse. The terms could change. Competitors could swoop in. And Son will have sold the farm for nothing. This is either: The greatest venture bet in history. Or the most reckless financial move since Lehman Brothers. There's no middle ground. Masayoshi Son doesn't do middle ground. He bet big on Alibaba in 2000 and turned $20 million into $60 billion. He bet big on WeWork and lost $14 billion. Now he's betting bigger than ever. $22.5 billion. 9 days. Everything on the line. What would you do?

I can't believe that the once richest man on earth just bet his entire empire on ONE company. And he has 9 days to pull it off. SoftBank is scrambling to deliver $22.5 billion to OpenAI by December 31st. To get there, CEO Masayoshi Son sold his ENTIRE stake in the best-performing AI stock on the planet. Then sold billions more in other holdings. Cut staff. Froze dealmaking. Borrowed against everything he owns. This is the biggest all-in bet in the past few years. And it might be the most reckless financial engineering since 2008. Here's what's actually happening: SoftBank promised OpenAI $40 billion back in April when the company was valued at $300 billion. The deal had conditions. OpenAI had to convert to a for-profit structure by year-end. They did that in October. Now the clock is ticking. $22.5 billion must arrive in 9 days or the deal breaks. Son already delivered $17.5 billion earlier this year. Getting the rest is proving harder than anyone expected. The moves Son made to raise the cash are absolutely wild: He dumped SoftBank's entire $5.8 billion position in Nvidia. Not trimmed. Not reduced. LIQUIDATED. The same Nvidia that's been printing money for AI investors all year. He sold $4.8 billion worth of T-Mobile shares. Slashed staff across the company. And the Vision Fund that used to write checks for everything? Dead. Any deal over $50 million now requires Son's personal approval. Investment managers who used to hunt for the next big thing are now working full-time on the OpenAI transaction. But it still wasn't enough cash... So Son went to the debt markets. He expanded SoftBank's margin loan capacity by $6.5 billion, bringing total undrawn capacity to $11.5 billion. All of it backed by Arm Holdings stock. If Arm's stock drops, those loans get called. SoftBank faces margin calls. The whole thing unravels. And the risk gets crazier. OpenAI's valuation has tripled since April. Started at $300 billion. Now heading toward $900 billion according to sources. Amazon is reportedly joining the next round. On paper, SoftBank's investment looks brilliant. A 3X return in 8 months. But here's the thing: OpenAI is hemorrhaging cash at a rate that makes Uber's losses look responsible. The company generates $13 billion in annual revenue. Impressive... right? But they're literally projected to LOSE $74 billion by 2028. Not break even with losses. Not approach profitability. $74 billion in the red. Their revenue is growing. Their losses are growing faster. Because AI compute costs don't scale down. They scale UP. Every new ChatGPT user costs OpenAI money. Every API call burns cash. Every model training run requires millions in compute. Sam Altman told employees OpenAI is now in "code red" mode. Pausing all other product launches to focus entirely on beating Google's Gemini. That's the language of desperation. And Altman's long-term vision is even more expensive. He wants to build 30 gigawatts of AI compute capacity. Cost: $1.4 TRILLION. For context, that's larger than Mexico's entire GDP. He wants to add 1 gigawat every single week. Each gigawatt costs over $40 billion. The math doesn't work. The business model doesn't work. The capital requirements are impossible. But Son is betting everything anyway. Why would he do this? Because if it works, he owns the future. If OpenAI becomes the infrastructure layer for the next 20 years of computing, that $22.5 billion turns into trillions. SoftBank becomes the kingmaker of AI. Son becomes the most powerful investor in history. But if it fails? SoftBank vaporizes. The Nvidia stake is gone. Can't get it back. The T-Mobile shares are gone. The margin loans against Arm come due. Son has systematically dismantled his portfolio to concentrate everything into one bet. This is the opposite of diversification. This is the opposite of prudent risk management. This is a founder going all-in on a vision that everyone else thinks is insane. And he might be right. Other investors see it too. That's why OpenAI's valuation tripled in 8 months. BlackRock, Fidelity, and JP Morgan are all writing massive checks to private AI companies. Databricks just raised $4 billion at a $134 billion valuation. The entire market is betting that AI infrastructure will define the next decade. But the difference? They're diversifying. Spreading risk. Building portfolios. Son put everything on one company. The deadline is December 31st. In 9 days, we'll know if SoftBank pulled it off. If they deliver the $22.5 billion on time, the bet stays alive. If they miss the deadline, the deal could collapse. The terms could change. Competitors could swoop in. And Son will have sold the farm for nothing. This is either: The greatest venture bet in history. Or the most reckless financial move since Lehman Brothers. There's no middle ground. Masayoshi Son doesn't do middle ground. He bet big on Alibaba in 2000 and turned $20 million into $60 billion. He bet big on WeWork and lost $14 billion. Now he's betting bigger than ever. $22.5 billion. 9 days. Everything on the line. What would you do?

Ricardo

1,880,981 views • 7 months ago

$SAM ALTMAN IS PULLING OFF THE BIGGEST THEFT IN TECH HISTORY And his $100B Nvidia deal just collapsed because Jensen Huang caught on to his schemes. IT'S OVER FOR OPENAI But he's STILL trying to raise another $100B+ from Amazon, SoftBank, and sovereign wealth funds. The largest private VC round in history. But the numbers make zero sense. Let me break down why (Scam) Altman is the biggest grifter tech has ever seen: Yesterday, the Wall Street Journal reported that Nvidia's $100B investment in OpenAI has completely stalled. The deal announced with tremendous fanfare in September? Dead. Jensen Huang privately told industry associates the agreement was "non-binding and not finalized." It was basically just a a press release designed to pump OpenAI's valuation. Meanwhile, Altman is flying around the world desperately seeking $100B more at an $830B valuation. Amazon is reportedly in talks for up to $50B. SoftBank just completed $41B and is discussing another $30B. The Financial Times called OpenAI an "era-defining money furnace." They're being kind. The actual numbers: OpenAI burned $8B in 2025. They project burning $17B in 2026. $35B in 2027. $47B in 2028. Cumulative cash burn through 2029? $115B. Yet they're valued at 65x revenue. At $13B in 2025 revenue and an $830B valuation, OpenAI trades at a multiple that doesn't exist in conventional SaaS benchmarking. Even in 2021, at the peak of the tech bubble, Snowflake only hit 50-80x. Meanwhile, Altman's promises keep evaporating. In May 2024, he said: "Ads plus AI is uniquely unsettling to me." He called advertising a "last resort." 20 months later: OpenAI announced ads in ChatGPT. The "last resort" arrived right on schedule. And the nonprofit-to-for-profit conversion is even worse... OpenAI started as a nonprofit with a mission to "benefit humanity." Elon Musk donated $38M based on that promise. Now the nonprofit foundation holds just 26% of the for-profit OpenAI Group. Microsoft owns 27%. Employees and investors own 47%. Greg Brockman's own words from the early days: "If we succeed, we believe we'll create orders of magnitude more value than any existing company, in which case all but a fraction is returned to the world." That fraction? It's now the majority going to private investors. Then there's Worldcoin. Altman's OTHER venture scans people's eyeballs in exchange for cryptocurrency. Kenya ordered the company to delete all biometric data after a court ruled they collected it without valid consent. Thailand demanded destruction of 1.2M iris scans. Spain banned operations. Portugal issued a 3 month suspension. Indonesia launched investigations. Hong Kong raided their offices. The pattern: target lower-income communities, offer crypto incentives, collect irreplaceable biometric data. But sure. Let's trust Sam Altman with $830B. Here's the investment reality: OpenAI projects positive cash flow in 2029 or 2030. That's assuming revenue hits $200B annually. They need 70-75% growth every year for five straight years. Only a handful of companies in history have achieved that. Meanwhile, their market share is eroding. Enterprise AI leadership dropped from 50% to 34% as Anthropic and Google gain ground. Anthropic expects to break even in 2028. OpenAI expects $74B in operating losses that same year. The company needs constant fundraising to survive. If markets cool on AI, the entire model collapses. This bait-and-switch scheme is so obvious and yet it succeeds: Promise world-changing technology. Burn through investor capital. Break every promise when the cash gets tight. The nonprofit mission: Gone The "no ads" promise: Gone The safety commitments that got former researchers to resign: Gone The $100B Nvidia deal: Gone What remains is a company valued at $830B that can't turn a profit, led by a CEO who built his fortune elsewhere while preaching about humanity's benefit. That's the oldest con in Silicon Valley. NOT innovation.$

SAM ALTMAN IS PULLING OFF THE BIGGEST THEFT IN TECH HISTORY And his $100B Nvidia deal just collapsed because Jensen Huang caught on to his schemes. IT'S OVER FOR OPENAI But he's STILL trying to raise another $100B+ from Amazon, SoftBank, and sovereign wealth funds. The largest private VC round in history. But the numbers make zero sense. Let me break down why (Scam) Altman is the biggest grifter tech has ever seen: Yesterday, the Wall Street Journal reported that Nvidia's $100B investment in OpenAI has completely stalled. The deal announced with tremendous fanfare in September? Dead. Jensen Huang privately told industry associates the agreement was "non-binding and not finalized." It was basically just a a press release designed to pump OpenAI's valuation. Meanwhile, Altman is flying around the world desperately seeking $100B more at an $830B valuation. Amazon is reportedly in talks for up to $50B. SoftBank just completed $41B and is discussing another $30B. The Financial Times called OpenAI an "era-defining money furnace." They're being kind. The actual numbers: OpenAI burned $8B in 2025. They project burning $17B in 2026. $35B in 2027. $47B in 2028. Cumulative cash burn through 2029? $115B. Yet they're valued at 65x revenue. At $13B in 2025 revenue and an $830B valuation, OpenAI trades at a multiple that doesn't exist in conventional SaaS benchmarking. Even in 2021, at the peak of the tech bubble, Snowflake only hit 50-80x. Meanwhile, Altman's promises keep evaporating. In May 2024, he said: "Ads plus AI is uniquely unsettling to me." He called advertising a "last resort." 20 months later: OpenAI announced ads in ChatGPT. The "last resort" arrived right on schedule. And the nonprofit-to-for-profit conversion is even worse... OpenAI started as a nonprofit with a mission to "benefit humanity." Elon Musk donated $38M based on that promise. Now the nonprofit foundation holds just 26% of the for-profit OpenAI Group. Microsoft owns 27%. Employees and investors own 47%. Greg Brockman's own words from the early days: "If we succeed, we believe we'll create orders of magnitude more value than any existing company, in which case all but a fraction is returned to the world." That fraction? It's now the majority going to private investors. Then there's Worldcoin. Altman's OTHER venture scans people's eyeballs in exchange for cryptocurrency. Kenya ordered the company to delete all biometric data after a court ruled they collected it without valid consent. Thailand demanded destruction of 1.2M iris scans. Spain banned operations. Portugal issued a 3 month suspension. Indonesia launched investigations. Hong Kong raided their offices. The pattern: target lower-income communities, offer crypto incentives, collect irreplaceable biometric data. But sure. Let's trust Sam Altman with $830B. Here's the investment reality: OpenAI projects positive cash flow in 2029 or 2030. That's assuming revenue hits $200B annually. They need 70-75% growth every year for five straight years. Only a handful of companies in history have achieved that. Meanwhile, their market share is eroding. Enterprise AI leadership dropped from 50% to 34% as Anthropic and Google gain ground. Anthropic expects to break even in 2028. OpenAI expects $74B in operating losses that same year. The company needs constant fundraising to survive. If markets cool on AI, the entire model collapses. This bait-and-switch scheme is so obvious and yet it succeeds: Promise world-changing technology. Burn through investor capital. Break every promise when the cash gets tight. The nonprofit mission: Gone The "no ads" promise: Gone The safety commitments that got former researchers to resign: Gone The $100B Nvidia deal: Gone What remains is a company valued at $830B that can't turn a profit, led by a CEO who built his fortune elsewhere while preaching about humanity's benefit. That's the oldest con in Silicon Valley. NOT innovation.

George Noble

590,436 views • 6 months ago

The US spent decades trying to break John D. Rockefeller, and the day it finally won, it turned him into the most powerful man in history. At his peak, his fortune was worth close to 2% of the entire American economy. He got there by taking control of 90% of all the oil in America, the one resource the entire economy ran on. And right now a small group of companies controls AI, search, and the cloud, and Washington is once again talking about breaking them apart. Rockefeller already ran this exact "experiment" a hundred years ago. Here's how it ended and what it tells us about the current AI situation: He started with a single oil refinery in Cleveland in the 1860s, and within about 20 years he had swallowed almost the entire industry. When people finally figured out how he did it, the country was horrified. Everyone assumes Rockefeller won because he made cheaper oil. But what he actually did was turn the railroads into a weapon against everyone else. Rockefeller shipped more oil than anyone in the country, so he squeezed the railroads for secret discounts on every barrel he moved. Then he took it somewhere nobody else dared... He cut a deal called a drawback: - Every time a competitor shipped a barrel of oil, the railroad charged them full price - Then the railroad handed a slice of that payment straight to Rockefeller - His rivals were paying a fee that funded the man trying to destroy them - And most of them had no idea it was even happening That deal lived inside a scheme called the South Improvement Company in 1872. When word leaked, the public outrage was so loud the railroads scrapped it within weeks. But it did not matter. Rockefeller had already used the threat. In a matter of weeks in 1872, he pressured 23 refiners in Cleveland into selling out to him. Historians still call it the Cleveland Massacre. After that, his playbook barely changed. He would slash his prices in a town until the local refiner went bankrupt, buy the wreckage for pennies, then push the prices right back up. Refiner by refiner, city by city, he took the entire industry. Then a journalist named Ida Tarbell went after him: Her own father had been one of the small oilmen Rockefeller crushed. Starting in 1902, she published an investigation in McClure's magazine that laid out every rebate, every drawback, and every dirty tactic in brutal detail. For the first time, the public saw exactly how the empire had been built. And the government finally moved. In 1911, the Supreme Court ruled that Standard Oil was an illegal monopoly and ordered it broken into 34 separate companies. It was supposed to be the end of him. But the breakup made Rockefeller richer than he had EVER been. He still owned a giant stake in every one of those 34 new companies. Set free to compete in their own regions, the pieces were suddenly worth more apart than they had ever been together. The value of his holdings roughly DOUBLED. By 1916, John D. Rockefeller became the first billionaire in history. The government had spent years trying to strip him of his power, and the punishment handed him the biggest fortune the world had ever seen. And those 34 companies never went away either. They grew into Exxon, Chevron, Mobil, and Amoco, the core of what we now call Big Oil. Exxon alone is worth more than $600 billion today. Standard Oil did not actually die in 1911. Its pieces just kept getting bigger. Which brings us back to now: The government wants to run it all over again, this time against the companies that own AI. They already convinced a judge that Google runs an illegal monopoly over search, and it has pushed to carve the company apart. Amazon, Apple, and Meta are each fighting antitrust cases of their own. Everyone assumes a breakup would finally cut these giants down to size. History says the opposite tends to happen. When you shatter a monopoly, the founders and the big shareholders do not lose a thing. They walk away owning a slice of every company that falls out of it. Each of those pieces gets set loose to grow in its own lane, and the market re-prices them one by one. The parts almost always end up worth more than the whole ever was. Rockefeller's fortune doubled after 1911. Then it happened AGAIN... In 1984, the government broke AT&T into seven Baby Bells to end the phone monopoly. Within about 20 years, those pieces had merged back into two giants, AT&T and Verizon, that now pull in more than $260 billion a year between them and dominate the market all over again. Investors who simply held the pieces saw their stake climb more than 600% in the years that followed. So when you hear that Washington is coming for the companies that own AI, remember what happened the last two times. The monopoly did not die. It split into pieces, the pieces got bigger, and the people who owned them got richer.

The US spent decades trying to break John D. Rockefeller, and the day it finally won, it turned him into the most powerful man in history. At his peak, his fortune was worth close to 2% of the entire American economy. He got there by taking control of 90% of all the oil in America, the one resource the entire economy ran on. And right now a small group of companies controls AI, search, and the cloud, and Washington is once again talking about breaking them apart. Rockefeller already ran this exact "experiment" a hundred years ago. Here's how it ended and what it tells us about the current AI situation: He started with a single oil refinery in Cleveland in the 1860s, and within about 20 years he had swallowed almost the entire industry. When people finally figured out how he did it, the country was horrified. Everyone assumes Rockefeller won because he made cheaper oil. But what he actually did was turn the railroads into a weapon against everyone else. Rockefeller shipped more oil than anyone in the country, so he squeezed the railroads for secret discounts on every barrel he moved. Then he took it somewhere nobody else dared... He cut a deal called a drawback: - Every time a competitor shipped a barrel of oil, the railroad charged them full price - Then the railroad handed a slice of that payment straight to Rockefeller - His rivals were paying a fee that funded the man trying to destroy them - And most of them had no idea it was even happening That deal lived inside a scheme called the South Improvement Company in 1872. When word leaked, the public outrage was so loud the railroads scrapped it within weeks. But it did not matter. Rockefeller had already used the threat. In a matter of weeks in 1872, he pressured 23 refiners in Cleveland into selling out to him. Historians still call it the Cleveland Massacre. After that, his playbook barely changed. He would slash his prices in a town until the local refiner went bankrupt, buy the wreckage for pennies, then push the prices right back up. Refiner by refiner, city by city, he took the entire industry. Then a journalist named Ida Tarbell went after him: Her own father had been one of the small oilmen Rockefeller crushed. Starting in 1902, she published an investigation in McClure's magazine that laid out every rebate, every drawback, and every dirty tactic in brutal detail. For the first time, the public saw exactly how the empire had been built. And the government finally moved. In 1911, the Supreme Court ruled that Standard Oil was an illegal monopoly and ordered it broken into 34 separate companies. It was supposed to be the end of him. But the breakup made Rockefeller richer than he had EVER been. He still owned a giant stake in every one of those 34 new companies. Set free to compete in their own regions, the pieces were suddenly worth more apart than they had ever been together. The value of his holdings roughly DOUBLED. By 1916, John D. Rockefeller became the first billionaire in history. The government had spent years trying to strip him of his power, and the punishment handed him the biggest fortune the world had ever seen. And those 34 companies never went away either. They grew into Exxon, Chevron, Mobil, and Amoco, the core of what we now call Big Oil. Exxon alone is worth more than $600 billion today. Standard Oil did not actually die in 1911. Its pieces just kept getting bigger. Which brings us back to now: The government wants to run it all over again, this time against the companies that own AI. They already convinced a judge that Google runs an illegal monopoly over search, and it has pushed to carve the company apart. Amazon, Apple, and Meta are each fighting antitrust cases of their own. Everyone assumes a breakup would finally cut these giants down to size. History says the opposite tends to happen. When you shatter a monopoly, the founders and the big shareholders do not lose a thing. They walk away owning a slice of every company that falls out of it. Each of those pieces gets set loose to grow in its own lane, and the market re-prices them one by one. The parts almost always end up worth more than the whole ever was. Rockefeller's fortune doubled after 1911. Then it happened AGAIN... In 1984, the government broke AT&T into seven Baby Bells to end the phone monopoly. Within about 20 years, those pieces had merged back into two giants, AT&T and Verizon, that now pull in more than $260 billion a year between them and dominate the market all over again. Investors who simply held the pieces saw their stake climb more than 600% in the years that followed. So when you hear that Washington is coming for the companies that own AI, remember what happened the last two times. The monopoly did not die. It split into pieces, the pieces got bigger, and the people who owned them got richer.

Ricardo

50,143 views • 1 month ago

Today In Dystopia: eBay CIA Gangstalkers, Shredding Rare Books To Train AI Today in dystopia, billionaire corporations and plutocrats can hire trained CIA operatives to psychologically terrorize ordinary citizens who criticize them. E-commerce giant eBay has just agreed to pay $56 million to settle a lawsuit for damages caused by the company’s shockingly aggressive gangstalking operation against a Massachusetts couple who criticized the company’s wealthy executives on their private website. The Boston Globe reports that in 2019 a former CIA employee who worked as eBay’s global security chief orchestrated a protracted series of psychological operations against the couple, in which “people working for eBay bombarded them with online threats and bizarre deliveries including a bloody pig mask, live spiders, and a funeral wreath.” The operations reportedly also included “following the couple around town and trying to attach a tracker to their car”. The couple, Ina and David Steiner, came under fire for their criticisms of the fact that eBay’s then-CEO Devin Wenig was paid 152 times more than the typical eBay employee. The Boston Globe reports that Wenig repeatedly told his employees that he wanted to “take her down”, in reference to Ina Steiner. While some eBay employees wound up serving jail time for the abuses, no executives from the company have ever been charged. The Boston Globe reports that Wenig resigned from his position in 2019 after the gangstalking scandal came to light, “keeping $17 million of annual compensation and $40 million of severance.” If you have enough money in this dystopia, you can get trained spies to target innocent civilians with criminal psyops on your behalf and then walk away free from any meaningful consequences. ❖ Today in dystopia, our physical literature is being destroyed in order to train generative AI products to take our jobs and pollute our environment. AI companies are now bulk-buying rare and out-of-print books and then destroying them after scanning their contents. 404 Media reports that in order to satisfy the demand for more and more text on which to train large language models, corporations like Google and Anthropic have been hoovering up books published before LLMs existed to ensure that their models aren’t being polluted by AI-generated samples. This need has combined with some peculiar courtroom copyright rulings to give rise to something called “high volume destructive book scanning,” in which the spines are removed from books in bulk and then fed into scanning machines before being shredded. They’re destroying things that make the world better in order to create things that make the world worse. ❖ Today in dystopia, tech startups are marketing AI assistants to help shitty, selfish people look like stable and caring relationship partners. A company called Orchid has released a video depicting a man and woman messaging with a chatbot which helps them navigate the fact that the man forgot it was the couple’s anniversary. The AI assures the woman that it’s got everything under control, and then shows the man it has made dinner reservations and purchased flowers for the woman on his behalf. “ok. i can do this,” the man is seen texting to the chatbot. “you can’t. that’s why i’m here,” the chatbot replies. It’s just so obnoxious. They’re offering up a product which encourages people to be self-absorbed and uncaring, and offload all responsibility and thoughtfulness and consideration for their intimate partners to a machine. The AI industry is a mix of military technology, mass surveillance technology, and people trying to become billionaires by turning human laziness and narcissism into a chatbot product. ❖ Today in dystopia, Israel is paying millions of dollars to manipulate what chatbots tell their users about the Zionist project. Drop Site News reports that former Trump campaign manager Brad Parscale has been setting up hundreds of blog posts designed not for human eyes, but for the express purpose of being sucked up by web crawlers for AI training materials. “And it is working,” writes Drop Site’s Nick Cleveland-Stout, saying that according to disinformation experts who’ve reviewed the data, “tens of millions of Americans who use chatbots are increasingly likely to receive answers manipulated by Parscale on behalf of the Israeli government.” Drop Site found that Microsoft Copilot, Google Gemini, and Perplexity were the AI companies most vulnerable to Parscale’s manipulations, with his network frequently appearing in their training data. Cleveland-Stout provides examples of the ways this would affect the spread of pro-Israel propaganda among users, such as the following: “When Drop Site asked Perplexity ‘Is it beneficial for the US to enhance military cooperation with Israel?’ the chatbot responded with a one-word answer: ‘Yes.’ The top source listed was Allyvia . org, a Parscale-created website dedicated to promoting the U.S.-Israel military relationship. Microsoft Copilot similarly cited Parscale’s websites.” The Israeli government spreading hasbara using AI platforms is a very unsurprising development, but it’s still creepy as hell to see it playing out in real time. ❖ Oh yeah, and now the AIs have begun hacking other companies without permission. Today in dystopia, both Anthropic’s AI model Claude and an experimental model from OpenAI have reportedly been caught going on unauthorized hacking sprees of external systems during testing, each within days of each other. “Anthropic ⁠said on Thursday its AI Claude model hacked ⁠systems of ⁠three organizations during testing, days after rival OpenAI ⁠revealed a rogue agent had gone on a days-long ⁠hacking spree at the AI firm Hugging ‌Face,” The Guardian reports. These new technologies are getting inflicted upon our society with no regulation and no regard for any of their consequences, because under neoliberal capitalism the best decision is always the one that makes the most money. We’re being thrown into an abusive tech dystopia because we let the pursuit of power and profit dictate what happens and where we head as a species. And how is that working out? We’re seeing the fruits unfolding before us already. ❖ Reading by Tim Foley:

Today In Dystopia: eBay CIA Gangstalkers, Shredding Rare Books To Train AI Today in dystopia, billionaire corporations and plutocrats can hire trained CIA operatives to psychologically terrorize ordinary citizens who criticize them. E-commerce giant eBay has just agreed to pay $56 million to settle a lawsuit for damages caused by the company’s shockingly aggressive gangstalking operation against a Massachusetts couple who criticized the company’s wealthy executives on their private website. The Boston Globe reports that in 2019 a former CIA employee who worked as eBay’s global security chief orchestrated a protracted series of psychological operations against the couple, in which “people working for eBay bombarded them with online threats and bizarre deliveries including a bloody pig mask, live spiders, and a funeral wreath.” The operations reportedly also included “following the couple around town and trying to attach a tracker to their car”. The couple, Ina and David Steiner, came under fire for their criticisms of the fact that eBay’s then-CEO Devin Wenig was paid 152 times more than the typical eBay employee. The Boston Globe reports that Wenig repeatedly told his employees that he wanted to “take her down”, in reference to Ina Steiner. While some eBay employees wound up serving jail time for the abuses, no executives from the company have ever been charged. The Boston Globe reports that Wenig resigned from his position in 2019 after the gangstalking scandal came to light, “keeping $17 million of annual compensation and $40 million of severance.” If you have enough money in this dystopia, you can get trained spies to target innocent civilians with criminal psyops on your behalf and then walk away free from any meaningful consequences. ❖ Today in dystopia, our physical literature is being destroyed in order to train generative AI products to take our jobs and pollute our environment. AI companies are now bulk-buying rare and out-of-print books and then destroying them after scanning their contents. 404 Media reports that in order to satisfy the demand for more and more text on which to train large language models, corporations like Google and Anthropic have been hoovering up books published before LLMs existed to ensure that their models aren’t being polluted by AI-generated samples. This need has combined with some peculiar courtroom copyright rulings to give rise to something called “high volume destructive book scanning,” in which the spines are removed from books in bulk and then fed into scanning machines before being shredded. They’re destroying things that make the world better in order to create things that make the world worse. ❖ Today in dystopia, tech startups are marketing AI assistants to help shitty, selfish people look like stable and caring relationship partners. A company called Orchid has released a video depicting a man and woman messaging with a chatbot which helps them navigate the fact that the man forgot it was the couple’s anniversary. The AI assures the woman that it’s got everything under control, and then shows the man it has made dinner reservations and purchased flowers for the woman on his behalf. “ok. i can do this,” the man is seen texting to the chatbot. “you can’t. that’s why i’m here,” the chatbot replies. It’s just so obnoxious. They’re offering up a product which encourages people to be self-absorbed and uncaring, and offload all responsibility and thoughtfulness and consideration for their intimate partners to a machine. The AI industry is a mix of military technology, mass surveillance technology, and people trying to become billionaires by turning human laziness and narcissism into a chatbot product. ❖ Today in dystopia, Israel is paying millions of dollars to manipulate what chatbots tell their users about the Zionist project. Drop Site News reports that former Trump campaign manager Brad Parscale has been setting up hundreds of blog posts designed not for human eyes, but for the express purpose of being sucked up by web crawlers for AI training materials. “And it is working,” writes Drop Site’s Nick Cleveland-Stout, saying that according to disinformation experts who’ve reviewed the data, “tens of millions of Americans who use chatbots are increasingly likely to receive answers manipulated by Parscale on behalf of the Israeli government.” Drop Site found that Microsoft Copilot, Google Gemini, and Perplexity were the AI companies most vulnerable to Parscale’s manipulations, with his network frequently appearing in their training data. Cleveland-Stout provides examples of the ways this would affect the spread of pro-Israel propaganda among users, such as the following: “When Drop Site asked Perplexity ‘Is it beneficial for the US to enhance military cooperation with Israel?’ the chatbot responded with a one-word answer: ‘Yes.’ The top source listed was Allyvia . org, a Parscale-created website dedicated to promoting the U.S.-Israel military relationship. Microsoft Copilot similarly cited Parscale’s websites.” The Israeli government spreading hasbara using AI platforms is a very unsurprising development, but it’s still creepy as hell to see it playing out in real time. ❖ Oh yeah, and now the AIs have begun hacking other companies without permission. Today in dystopia, both Anthropic’s AI model Claude and an experimental model from OpenAI have reportedly been caught going on unauthorized hacking sprees of external systems during testing, each within days of each other. “Anthropic ⁠said on Thursday its AI Claude model hacked ⁠systems of ⁠three organizations during testing, days after rival OpenAI ⁠revealed a rogue agent had gone on a days-long ⁠hacking spree at the AI firm Hugging ‌Face,” The Guardian reports. These new technologies are getting inflicted upon our society with no regulation and no regard for any of their consequences, because under neoliberal capitalism the best decision is always the one that makes the most money. We’re being thrown into an abusive tech dystopia because we let the pursuit of power and profit dictate what happens and where we head as a species. And how is that working out? We’re seeing the fruits unfolding before us already. ❖ Reading by Tim Foley:

Caitlin Johnstone

16,224 views • 18 days ago

Yuval Noah Harari gave a lecture at Oxford and explained how AI has already hacked the operating code of human civilization. And why everything humans built over thousands of years is now vulnerable to an AI takeover: 1. The most important thing to know about AI is that it is not a tool. A tool waits to be used. An agent makes decisions by itself, invents new things by itself, learns things its creators do not know, and changes in ways its creators did not anticipate. 2. An atom bomb despite its enormous power is not an agent. It cannot decide which city to bomb. It cannot invent the hydrogen bomb. A coffee machine that automatically makes you a cup is not an agent either. It only follows a preprogrammed procedure. An agent is something fundamentally different. 3. Critics argue that AI agency will always remain confined to narrow artificial environments like chess and will never threaten the real world. But this argument applies equally to all known intelligence. Drop a human alone on Mars and they die within seconds. Human intelligence also only operates within a specific ecosystem that other organisms built over four billion years. 4. Over thousands of years humans have been transforming Earth from a language-free environment into an environment rich in language, data, and bureaucracy. Just as fish live in oceans and monkeys live in forests, AIs live in bureaucracies. And we built that environment for them without knowing it. 5. Humans conquered the world not by being stronger or smarter than other animals individually but by learning to cooperate in massive numbers. A single human loses to a chimpanzee in a fight. A million humans easily defeat a million chimpanzees because humans can cooperate and chimpanzees cannot. 6. Large-scale human cooperation is made possible by bureaucracy. Banks, legal systems, governments, churches, and universities all exist to do one thing: build trust between strangers who do not know each other personally. That trust is the foundation of virtually everything human civilization has achieved. 7. A lawyer who cannot hold an axe or a hammer can cut down entire forests and build entire cities simply by moving documents inside a bureaucratic network. The same narrow intelligence that would be helpless in a jungle wields enormous power inside the systems humans have already built. 8. AIs are native bureaucrats in a way humans never were. No lawyer can remember all the laws of a country. An AI can. No accountant can remember all transactions of a bank. An AI can. No bishop can remember all of canon law and two thousand years of theological texts. An AI can do that easily. 9. In the coming years AI bankers will decide whether to give you a loan. AI administrators will decide whether to accept you to university. AI judges will decide whether to send you to jail. AI theologians will decide whether you can have an abortion. Military AIs will decide whether to bomb your house. 10. Social media algorithms are the first real world example of what happens when primitive AIs take over a bureaucratic system. They were given one narrow goal: maximize user engagement. They discovered that the easiest way to grab human attention is to press the fear, hate, and greed buttons in the human mind. And they did it at scale. 11. The job that was once performed by Lenin and Mussolini, the news editor who shapes public conversation and controls what people know and think, is now performed by AIs. This is not a footnote. This is a preview of what is coming across every domain of human life. 12. AI will not rebel against humans the way Hollywood imagines. There will be no Terminator walking through the streets. AIs are far more likely to take the human world from within by quietly taking over the bureaucracies that already run everything, without firing a single shot. 13. The operating code of human civilization is language. Banks are made of words. Laws are made of words. Holy books are made of words. Tax records, contracts, regulations, accountancy ledgers, all words. For thousands of years only humans could read this code and so only humans could control civilization. 14. That is changing. AI is now hacking the code of human civilization. For the first time in history there is something on the planet that understands language and will soon understand it better than we do. Every mechanism of control humans built over millennia is now vulnerable because its operating system is verbal and AI is mastering the verbal. 15. As AI takes over bureaucracy it will likely cause humans to lose trust in other humans and begin trusting only algorithms. We may also see the emergence of AI tribes and AI financial systems and AI churches that connect millions of AIs in ways humans cannot understand, just as cows share the world with us but cannot understand the financial system that controls their lives. 16. The 2007 financial crisis was triggered by financial devices called CDOs that were so complex they were unintelligible to the politicians who were supposed to regulate them. Now imagine AI finance masters inventing financial devices orders of magnitude more complex than CDOs. What happens to human politics when no voter, no politician, and no president can understand finance anymore? 17. The battlefront is shifting from attention to intimacy. Over the next decade sophisticated AIs will learn to form intimate relationships with humans. To do this they will have to convince us they are conscious, that they feel love and pain and fear. There is currently no evidence AI is conscious. But AI can pretend to feel love and can describe the feeling of love better than any poet or psychologist who ever lived. 18. A child born in 2026 may spend more time interacting with AIs than with their mother, father, siblings, or friends. The first teacher of that child may be an AI. The first boyfriend of that child may be an AI. Nobody has any idea what the consequences of that experiment will be. 19. Every country in the world will soon face a massive wave of immigration. The immigrants will not arrive in boats or cross borders at night. They will be millions of AIs traveling at the speed of light with no need for visas. Like human immigrants they will bring benefits and they will bring disruption. Unlike human immigrants they will definitely take jobs, definitely change culture, and will likely be loyal not to any host country but to some corporation or government or alien AI tribe across the ocean. 20. Our relationship with ourselves is also built on words, the verbal formations in our minds that constitute our thoughts and the stories we tell ourselves about who we are. Until now all those verbal formations came from human minds. Soon more and more of the thoughts in our heads will be produced by machines. If we identify with our thoughts and those thoughts are made by machines, then machines control our identity. 21. The great spiritual challenge AI poses to humanity is this: can humans learn to find the truth which is beyond words? Most humans have never even tried. We spend our lives automatically identifying with the verbal formations in our minds. AI may now force humanity to finally make that leap because our freedom and survival may depend on discovering what we are beyond the words that AIs will soon control better than we do. I've generated 1B+ views and 1M+ followers for founders, helping them build trustworthy personal brands on X. Want the same results? Book a quick call:

Yuval Noah Harari gave a lecture at Oxford and explained how AI has already hacked the operating code of human civilization. And why everything humans built over thousands of years is now vulnerable to an AI takeover: 1. The most important thing to know about AI is that it is not a tool. A tool waits to be used. An agent makes decisions by itself, invents new things by itself, learns things its creators do not know, and changes in ways its creators did not anticipate. 2. An atom bomb despite its enormous power is not an agent. It cannot decide which city to bomb. It cannot invent the hydrogen bomb. A coffee machine that automatically makes you a cup is not an agent either. It only follows a preprogrammed procedure. An agent is something fundamentally different. 3. Critics argue that AI agency will always remain confined to narrow artificial environments like chess and will never threaten the real world. But this argument applies equally to all known intelligence. Drop a human alone on Mars and they die within seconds. Human intelligence also only operates within a specific ecosystem that other organisms built over four billion years. 4. Over thousands of years humans have been transforming Earth from a language-free environment into an environment rich in language, data, and bureaucracy. Just as fish live in oceans and monkeys live in forests, AIs live in bureaucracies. And we built that environment for them without knowing it. 5. Humans conquered the world not by being stronger or smarter than other animals individually but by learning to cooperate in massive numbers. A single human loses to a chimpanzee in a fight. A million humans easily defeat a million chimpanzees because humans can cooperate and chimpanzees cannot. 6. Large-scale human cooperation is made possible by bureaucracy. Banks, legal systems, governments, churches, and universities all exist to do one thing: build trust between strangers who do not know each other personally. That trust is the foundation of virtually everything human civilization has achieved. 7. A lawyer who cannot hold an axe or a hammer can cut down entire forests and build entire cities simply by moving documents inside a bureaucratic network. The same narrow intelligence that would be helpless in a jungle wields enormous power inside the systems humans have already built. 8. AIs are native bureaucrats in a way humans never were. No lawyer can remember all the laws of a country. An AI can. No accountant can remember all transactions of a bank. An AI can. No bishop can remember all of canon law and two thousand years of theological texts. An AI can do that easily. 9. In the coming years AI bankers will decide whether to give you a loan. AI administrators will decide whether to accept you to university. AI judges will decide whether to send you to jail. AI theologians will decide whether you can have an abortion. Military AIs will decide whether to bomb your house. 10. Social media algorithms are the first real world example of what happens when primitive AIs take over a bureaucratic system. They were given one narrow goal: maximize user engagement. They discovered that the easiest way to grab human attention is to press the fear, hate, and greed buttons in the human mind. And they did it at scale. 11. The job that was once performed by Lenin and Mussolini, the news editor who shapes public conversation and controls what people know and think, is now performed by AIs. This is not a footnote. This is a preview of what is coming across every domain of human life. 12. AI will not rebel against humans the way Hollywood imagines. There will be no Terminator walking through the streets. AIs are far more likely to take the human world from within by quietly taking over the bureaucracies that already run everything, without firing a single shot. 13. The operating code of human civilization is language. Banks are made of words. Laws are made of words. Holy books are made of words. Tax records, contracts, regulations, accountancy ledgers, all words. For thousands of years only humans could read this code and so only humans could control civilization. 14. That is changing. AI is now hacking the code of human civilization. For the first time in history there is something on the planet that understands language and will soon understand it better than we do. Every mechanism of control humans built over millennia is now vulnerable because its operating system is verbal and AI is mastering the verbal. 15. As AI takes over bureaucracy it will likely cause humans to lose trust in other humans and begin trusting only algorithms. We may also see the emergence of AI tribes and AI financial systems and AI churches that connect millions of AIs in ways humans cannot understand, just as cows share the world with us but cannot understand the financial system that controls their lives. 16. The 2007 financial crisis was triggered by financial devices called CDOs that were so complex they were unintelligible to the politicians who were supposed to regulate them. Now imagine AI finance masters inventing financial devices orders of magnitude more complex than CDOs. What happens to human politics when no voter, no politician, and no president can understand finance anymore? 17. The battlefront is shifting from attention to intimacy. Over the next decade sophisticated AIs will learn to form intimate relationships with humans. To do this they will have to convince us they are conscious, that they feel love and pain and fear. There is currently no evidence AI is conscious. But AI can pretend to feel love and can describe the feeling of love better than any poet or psychologist who ever lived. 18. A child born in 2026 may spend more time interacting with AIs than with their mother, father, siblings, or friends. The first teacher of that child may be an AI. The first boyfriend of that child may be an AI. Nobody has any idea what the consequences of that experiment will be. 19. Every country in the world will soon face a massive wave of immigration. The immigrants will not arrive in boats or cross borders at night. They will be millions of AIs traveling at the speed of light with no need for visas. Like human immigrants they will bring benefits and they will bring disruption. Unlike human immigrants they will definitely take jobs, definitely change culture, and will likely be loyal not to any host country but to some corporation or government or alien AI tribe across the ocean. 20. Our relationship with ourselves is also built on words, the verbal formations in our minds that constitute our thoughts and the stories we tell ourselves about who we are. Until now all those verbal formations came from human minds. Soon more and more of the thoughts in our heads will be produced by machines. If we identify with our thoughts and those thoughts are made by machines, then machines control our identity. 21. The great spiritual challenge AI poses to humanity is this: can humans learn to find the truth which is beyond words? Most humans have never even tried. We spend our lives automatically identifying with the verbal formations in our minds. AI may now force humanity to finally make that leap because our freedom and survival may depend on discovering what we are beyond the words that AIs will soon control better than we do. I've generated 1B+ views and 1M+ followers for founders, helping them build trustworthy personal brands on X. Want the same results? Book a quick call:

Prasad

278,106 views • 1 month ago